textomap

Hey Hackers, Textomap has been nominated in HackerNoon's annual Startups of The Year awards in Berlin, Germany.. Please vote for us here: https://hackernoon.com/startups/europe/europe-berlin-germany?stup=66f326566ea4677e23e35644&embedable=true Read more about us below to understand why we deserve your vote. Meet Textomap Creating interactive maps for location based content and educational material can be a complex and time-consuming task. Textomap simplifies this process by using AI to transform location-based text into interactive maps within seconds. This allows businesses, content creators, and educators. to easily create, customize, and embed maps on their websites, helping to improve the browsing experience with interactive guides, relevant data, and links to additional resources. How Textomap achieved product-market fit Maps are an inseparable part of understanding location based content, yet they remain complex and time consuming to create. We knew that Textomap could benedit many types of industriess We launched an MVP in early 2023 which was free and open to the public. We received great feedback from people in the travel sector and launched a paid subscription so users could start creating and embedding maps into their websites and content. As for market size, together with hundreds of thousands of travel businesses and creators, we’re also providing solutions to our customers from the education, real estate, event planning and news media sectors. We’ve also been contacted by a very large company with a substantial market hold to see where we can cooperate. The evolution of Textomap We began our journey with a focus on travel content—it was a natural fit for us as passionate travelers. However, we designed Textomap to be versatile, recognizing that storytellers and educators in various fields could benefit from it too. Today, we have users across multiple sectors, and we’re continuously enhancing Textomap based on their feedback and unique needs. We work closely with our users, grateful to have them as active partners in shaping and improving Textomap. Milestones and achievements Over 100,000 maps have been created with Textomap. We already have 10,000 signed-up users with many paying customers. We’re currently growing organically and fine-tuning our product market fit. We’re getting great attention and media coverage from many bloggers, online directories and also large tech news outlets like Phocuswire, Hackernoon and the biggest German tech magazine “CT.” We’ve also won some awards for educational tool of the year and have been name a top startup by Travel Massive and geoawesomeness. Lessons learned Keep an open mind and listen to your users. Let your users help guide you in the right direction, do not get caught up in early assumptions. Create experiences and solutions based on real problems and provide the solution with the person you’re building it for in mind. What Startups of The Year means to us We’re hoping to be a part this great initiative, to get inspired and hopefully inspire others by exposing Textomap to those who could benefit from using it Conclusion We’re looking forward to another exciting year with many great ideas, improvements and developments. Stay tuned! Vote for us today! Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here.
Want to nominate a startup? Follow the steps here.Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Hey Hackers, Textomap has been nominated in HackerNoon's annual Startups of The Year awards in Berlin, Germany.. Please vote for us here: Please vote for us here: https://hackernoon.com/startups/europe/europe-berlin-germany?stup=66f326566ea4677e23e35644&embedable=true https://hackernoon.com/startups/europe/europe-berlin-germany?stup=66f326566ea4677e23e35644&embedable=true Read more about us below to understand why we deserve your vote. Meet Textomap Meet Textomap Creating interactive maps for location based content and educational material can be a complex and time-consuming task. Textomap simplifies this process by using AI to transform location-based text into interactive maps within seconds. This allows businesses, content creators, and educators. to easily create, customize, and embed maps on their websites, helping to improve the browsing experience with interactive guides, relevant data, and links to additional resources. How Textomap achieved product-market fit How Textomap achieved product-market fit Maps are an inseparable part of understanding location based content, yet they remain complex and time consuming to create. We knew that Textomap could benedit many types of industriess We launched an MVP in early 2023 which was free and open to the public. We received great feedback from people in the travel sector and launched a paid subscription so users could start creating and embedding maps into their websites and content. As for market size, together with hundreds of thousands of travel businesses and creators, we’re also providing solutions to our customers from the education, real estate, event planning and news media sectors. We’ve also been contacted by a very large company with a substantial market hold to see where we can cooperate. The evolution of Textomap The evolution of Textomap We began our journey with a focus on travel content—it was a natural fit for us as passionate travelers. However, we designed Textomap to be versatile, recognizing that storytellers and educators in various fields could benefit from it too. Today, we have users across multiple sectors, and we’re continuously enhancing Textomap based on their feedback and unique needs. We work closely with our users, grateful to have them as active partners in shaping and improving Textomap. Milestones and achievements Milestones and achievements Over 100,000 maps have been created with Textomap. We already have 10,000 signed-up users with many paying customers. We’re currently growing organically and fine-tuning our product market fit. We’re getting great attention and media coverage from many bloggers, online directories and also large tech news outlets like Phocuswire, Hackernoon and the biggest German tech magazine “CT.” We’ve also won some awards for educational tool of the year and have been name a top startup by Travel Massive and geoawesomeness. Lessons learned Lessons learned Keep an open mind and listen to your users. Let your users help guide you in the right direction, do not get caught up in early assumptions. Create experiences and solutions based on real problems and provide the solution with the person you’re building it for in mind. What Startups of The Year means to us What Startups of The Year means to us We’re hoping to be a part this great initiative, to get inspired and hopefully inspire others by exposing Textomap to those who could benefit from using it Conclusion Conclusion We’re looking forward to another exciting year with many great ideas, improvements and developments. Stay tuned! Vote for us today! Vote for us today ! Vote for us today Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here. Want to nominate a startup? Follow the steps here. Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Welcome to HackerNoon’s Startups of The Year 2024 interview series, spotlighting startups from around the world that are changing the way we live, one solution at a time. If you’ve been nominated, create a brand profile and answer these questions here . Startups of The Year 2024 create a brand profile create a brand profile create a brand profile here here Want to nominate a startup? Follow the steps here . here here Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here, here, and here. Looking for inspiration? Check out how other startups responded to last year’s Startups of The Year interview questions and examples of company responses here , here , and here . last year’s Startups of The Year interview questions last year’s Startups of The Year interview questions here here here here here here

Meet Textomap, Startups of the Year 2024 Nominee

2024 has been a year full of changes and innovations - a massive year for the world, and a massive year for us, as Startups of The Year 2024 has been the biggest campaign yet for HackerNoon! With 150,000+ startups nominated across the globe and over 4 million votes cast, it is finally time for the results to be revealed. A round of applause for the winners of the Education Industry! 150,000+ startups 150,000+ startups 150,000+ startups 4 million votes cast 4 million votes cast Education Industry Education has always been a crucial industry and a pioneer for innovative changes. In 2024, the Education industry has experienced groundbreaking transformations, driven by tech advancements and AI integrations for a more personalized learning experience. Educational institutions are putting emphasis on community-based learning and developing critical thinking and soft skills, utilizing smarter algorithms to make knowledge more effective and accessible. Education 🏆 Key Stats Let’s start out with some general stats for all of you technical folks. Total Startups Participated: 34,300
Sub Industries Represented: 8
Total Votes Gathered: 34,200
Winning Startups: 8 Total Startups Participated: 34,300 Total Startups Participated: Sub Industries Represented: 8 Sub Industries Represented: Total Votes Gathered: 34,200 Total Votes Gathered: Winning Startups: 8 Winning Startups: To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner.


You may also check out the full list of nominated startups in the Education Industry HERE.



Stay tuned for our Startups of The Year Winner Announcement Series, where we’ll be highlighting the top startups across various regions and industries. To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner.


You may also check out the full list of nominated startups in the Education Industry HERE. To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner. To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner. startups.hackernoon.com You may also check out the full list of nominated startups in the Education Industry HERE. You may also check out the full list of nominated startups in the Education Industry HERE. HERE. HERE Stay tuned for our Startups of The Year Winner Announcement Series, where we’ll be highlighting the top startups across various regions and industries. Stay tuned for our Startups of The Year Winner Announcement Series, where we’ll be highlighting the top startups across various regions and industries. Startups of The Year Winner Announcement Series Now, drum roll please, here are all the 2024 Startups of The Year winners for Education drum roll please Education Research (11.3k total votes, 6.2k startups) Research Winner: Nat5 Winner: Nat5 Nat5 SNATIKA
Lite-1 SNATIKA SNATIKA Lite-1 Lite-1 Honorable mentions: Honorable mentions: SimZero
Quatfit
EcoScience Lab
7Analytics
Brandenburg Labs GmbH
Niche Report
TechBairn SimZero SimZero Quatfit Quatfit EcoScience Lab EcoScience Lab 7Analytics 7Analytics Brandenburg Labs GmbH Brandenburg Labs GmbH Niche Report Niche Report TechBairn TechBairn Training And Consulting (6.7k total votes, 12.7k startups) Training And Consulting Winner: SNATIKA Winner: SNATIKA SNATIKA The BD School
Coffey & Consult The BD School The BD School Coffey & Consult Coffey & Consult Honorable mentions: Honorable mentions: Byte Splash Software Training and Placement Center
CherryOnTech
FEMSTECH Worldwide e.V.
Iniciativa Proxima
Edward Consulting
Quality New Zealand Education Limited
NowEdge Byte Splash Software Training and Placement Center Byte Splash Software Training and Placement Center CherryOnTech CherryOnTech FEMSTECH Worldwide e.V. FEMSTECH Worldwide e.V. Iniciativa Proxima Iniciativa Proxima Edward Consulting Edward Consulting Quality New Zealand Education Limited Quality New Zealand Education Limited NowEdge NowEdge E-Learning (5.1k total votes, 3.4k startups) E-Learning Winner: textomap Winner: textomap textomap Wellbeing Think Tank
Cadence Infotech Wellbeing Think Tank Wellbeing Think Tank Cadence Infotech Cadence Infotech Honorable mentions: Honorable mentions: Sphiderass Web LTD
svexa
FEMSTECH Worldwide e.V.
D.notitia
Linguado
Kocha Hub
Undertow Sphiderass Web LTD Sphiderass Web LTD svexa svexa FEMSTECH Worldwide e.V. FEMSTECH Worldwide e.V. D.notitia D.notitia Linguado Linguado Kocha Hub Kocha Hub Undertow Undertow Educational Institutions (3.8k total votes, 3.7k startups) Educational Institutions Winner: Quality New Zealand Education Limited Winner: Quality New Zealand Education Limited Quality New Zealand Education Limited SNATIKA
Polygence SNATIKA SNATIKA Polygence Polygence Honorable mentions: Honorable mentions: EDUrain Inc. (Techstars ‘23)
Abhilekh Verma Consultancy (OPC) Private Limited
Founder University
Student Village Academy
Youth of Canada
Iniciativa Startup Experience
Bettre Institute EDUrain Inc. (Techstars ‘23) EDUrain Inc. (Techstars ‘23) Abhilekh Verma Consultancy (OPC) Private Limited Abhilekh Verma Consultancy (OPC) Private Limited Founder University Founder University Student Village Academy Student Village Academy Youth of Canada Youth of Canada Iniciativa Startup Experience Iniciativa Startup Experience Bettre Institute Bettre Institute Administrative (3.1k total votes, 4.1k startups) Administrative Winner: Iniciativa Proxima Winner: Iniciativa Proxima Iniciativa Proxima Bokonzi
Treeback Bokonzi Bokonzi Treeback Treeback Honorable mentions: Honorable mentions: Watergenics
Edward Consulting
H2UB
ReFi Medellín
Employment Express Verband LLP
Terrenity
IDEALERS B2B PVT LTD Watergenics Watergenics Edward Consulting Edward Consulting H2UB H2UB ReFi Medellín ReFi Medellín Employment Express Verband LLP Employment Express Verband LLP Terrenity Terrenity IDEALERS B2B PVT LTD IDEALERS B2B PVT LTD Edtech (2.2k total votes, 2.2k startups) Edtech Winner: D.notitia Winner: D.notitia D.notitia SKL.vc
Bokonzi SKL.vc SKL.vc Bokonzi Bokonzi Honorable mentions: Honorable mentions: DevStacks
Linguado
Kocha Hub
bylittle Learning
Hazabarolo.com (হ য ব র ল.কম)
Golden Celestial Ratio
CodersCave DevStacks DevStacks Linguado Linguado Kocha Hub Kocha Hub bylittle Learning bylittle Learning Hazabarolo.com (হ য ব র ল.কম) Hazabarolo.com (হ য ব র ল.কম) Golden Celestial Ratio Golden Celestial Ratio CodersCave CodersCave Think Tanks (1.1k total votes, 400 startups) Think Tanks Winner: Gildre Winner: Gildre Gildre Wellbeing Think Tank
H2UB Wellbeing Think Tank Wellbeing Think Tank H2UB H2UB Honorable mentions: Honorable mentions: PORSESH POLICY RESEARCH INSTITUTE
Centre for Annihilation of Caste
What The Hack
Panna
SDR Leaders of EMEA
San Diego Regional Policy & Innovation Center
Cameroon Economic Policy Institute (CEPI) PORSESH POLICY RESEARCH INSTITUTE PORSESH POLICY RESEARCH INSTITUTE Centre for Annihilation of Caste Centre for Annihilation of Caste What The Hack What The Hack Panna Panna SDR Leaders of EMEA SDR Leaders of EMEA San Diego Regional Policy & Innovation Center San Diego Regional Policy & Innovation Center Cameroon Economic Policy Institute (CEPI) Cameroon Economic Policy Institute (CEPI) Cultural Institutions (898 total votes, 1.6k startups) Cultural Institutions Winner: Seneca Foundation Winner: Seneca Foundation Seneca Foundation Jamshedpur Queer Circle
AMBA FINANCE UGANDA LTD Jamshedpur Queer Circle Jamshedpur Queer Circle AMBA FINANCE UGANDA LTD AMBA FINANCE UGANDA LTD Honorable mentions: Honorable mentions: Resilient Cities Network
mindfulstartup.school
MiDesk Global
WiBT Women in Blockchain Talks
International Mentoring Program | St. Louis
The MOBI Trust
Bridging Tech Resilient Cities Network Resilient Cities Network mindfulstartup.school mindfulstartup.school MiDesk Global MiDesk Global WiBT Women in Blockchain Talks WiBT Women in Blockchain Talks International Mentoring Program | St. Louis International Mentoring Program | St. Louis The MOBI Trust The MOBI Trust Bridging Tech Bridging Tech Congratulations to you all! We will contact you with details on how to claim your winnings! Congratulations to you all! We will contact you with details on how to claim your winnings! Congratulations to you all! We will contact you with details on how to claim your winnings! See the global regional announcements here.
See the global industry announcements here. See the global regional announcements here.
See the global industry announcements here. See the global regional announcements here. here See the global industry announcements here. here About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries participated in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many storieshave been written about these daring and rising startups. Startups of The Year 2024 many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview Evergreen Tech Company News Visit our FAQ page to learn more. FAQ Download our design assets here. here Check out the Startups of The Year Merch Shop here. here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated packages to solve your marketing challenges. Book a meeting with us to learn more! curated packages Book a meeting with us to learn more! Book a meeting with us to learn more! Meet our sponsors: Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool.Get your offer now! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free. Hubspot: Get started for free Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform

Startups of The Year 2024 Winners: Education

Стартапы 2024 года пераможцы: адукацыя

Iniciatives de l'any 2024 Guanyadors: Educació

Startups des Jahres 2024 Gewinner: Bildung

Startups del Año 2024 Ganadores: Educación

Startupovi godine 2024 pobjednici: obrazovanje

Startup Tahun 2024 Pemenang: Pendidikan

Startups of the Year 2024 Winners: 教育

Pamba la Pamba la Pamba la 2024: Education

Startups ຂອງປີ 2024 ຜູ້ຊ່ຽວຊານ: ການສຶກສາ

Startups do Ano 2024 vencedores: Educação

2024 වසරේ Startups ජයග්රාහකයින්: අධ් යාපනය

Переможці стартапів 2024 року: освіта

After months of nominations, voting, and community support, the Startups of The Year 2024 results are in. With over 150,000 startups in the running and more than 4 million votes cast, this year’s awards have been our biggest yet, and the AI Industry, in particular, was on fire. Startups of The Year 2024 Startups of The Year 2024 150,000 startups 150,000 startups 4 million votes The AI startup scene continues to evolve at breakneck speed, spurred by advances in deep learning, ambitious teams, and real-world impact across industries. From intelligent automation to next-gen developer tools, the startups you voted for are pushing the boundaries of what’s possible. Let’s take a look at the standout AI startups of 2024. AI startups Startups of The Year 2024: Key AI Industry Stats For the number lovers out there, here’s a quick breakdown: For the number lovers out there, here’s a quick breakdown: Total Number of Participating Startups: 18,519
Sub Industries Represented: 8
Total Votes Recorded: 288,700
Winning Startups: 8 Total Number of Participating Startups: 18,519 Total Number of Participating Startups: Sub Industries Represented: 8 Sub Industries Represented: Total Votes Recorded: 288,700 Total Votes Recorded: Winning Startups: 8 Winning Startups: To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner.


You may also check out the full list of nominated startups in the AI Industry HERE.



Stay tuned for our Startups of The Year Winner Announcement Series, where we’ll be highlighting the top startups across various regions and industries. To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner.


You may also check out the full list of nominated startups in the AI Industry HERE. To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner. To explore winning top startups in other industries or cities, head over to startups.hackernoon.com and use the search bar — the name at the top of each list is the winner. startups.hackernoon.com You may also check out the full list of nominated startups in the AI Industry HERE. You may also check out the full list of nominated startups in the AI Industry HERE. HERE. HERE Stay tuned for our Startups of The Year Winner Announcement Series, where we’ll be highlighting the top startups across various regions and industries. Stay tuned for our Startups of The Year Winner Announcement Series, where we’ll be highlighting the top startups across various regions and industries. Startups of The Year Winner Announcement Series Now, drum roll please… Now, drum roll please… Meet the Top AI Startups of The Year 2024 AI Startups Analytics (142.4k total votes, 2.1k startups) Analytics Winner: Mecanizou Winner: Mecanizou Mecanizou ViralMango - Influencer Marketing
Nat5 ViralMango - Influencer Marketing ViralMango - Influencer Marketing Nat5 Nat5 Honorable mentions: Honorable mentions: AKUMENIA
Hyperhumans
Business Intelligence Limited
Reputation House
7Analytics
Mazmobi
Recut URL Shortener AKUMENIA AKUMENIA Hyperhumans Hyperhumans Business Intelligence Limited Business Intelligence Limited Reputation House Reputation House 7Analytics 7Analytics Mazmobi Mazmobi Recut URL Shortener Recut URL Shortener Automation (67.4k total votes, 1.4k startups) Automation Winner: Tezeract Winner: Tezeract Tezeract autobotAI
Sereda.ai autobotAI autobotAI Sereda.ai Sereda.ai Honorable mentions: Honorable mentions: The Real Group
RentBamboo
Yemberzal
Accredify
Maiky
Hyperce
QOD Information Technology The Real Group The Real Group RentBamboo RentBamboo Yemberzal Yemberzal Accredify Accredify Maiky Maiky Hyperce Hyperce QOD Information Technology QOD Information Technology Business Intelligence (35.6k total votes, 12.1k startups) Business Intelligence Winner: Leonado Limited Winner: Leonado Limited Leonado Limited Tezeract
Mecanizou Tezeract Tezeract Mecanizou Mecanizou Honorable mentions: Honorable mentions: KD Squares
AQUi9
Postjer Group
Unirises
DataMind
Entrustech Inc.
Matter IT Mauritanie KD Squares KD Squares AQUi9 AQUi9 Postjer Group Postjer Group Unirises Unirises DataMind DataMind Entrustech Inc. Entrustech Inc. Matter IT Mauritanie Matter IT Mauritanie Machine Learning (22.7k total votes, 1k startups) Machine Learning Winner: Didit Winner: Didit Didit Antix Interactive Inc.
Hoken Tech Antix Interactive Inc. Antix Interactive Inc. Hoken Tech Hoken Tech Honorable mentions: Honorable mentions: AI Verse
Epowar
FueGo.
SimZero
Quatfit
Ac28R
Hidonix AI Verse AI Verse Epowar Epowar FueGo. FueGo. SimZero SimZero Quatfit Quatfit Ac28R Ac28R Hidonix Hidonix Generative AI (15.5k total votes, 235 startups) Generative AI Winner: Worksible Winner: Worksible Worksible Tezeract
Antix Interactive Inc. Tezeract Tezeract Antix Interactive Inc. Antix Interactive Inc. Honorable mentions: Honorable mentions: Pieces for Developers
Arize Phoenix
textomap
Ac28R
mkinf
Sivi
Vcodewonders Pieces for Developers Pieces for Developers Arize Phoenix Arize Phoenix textomap textomap Ac28R Ac28R mkinf mkinf Sivi Sivi Vcodewonders Vcodewonders AI Wrappers (2.5k total votes, 192 startups) AI Wrappers Winner: Sereda.ai Winner: Sereda.ai Sereda.ai FueGo.
Shugert Marketing FueGo. FueGo. Shugert Marketing Shugert Marketing Honorable mentions: Honorable mentions: Cabina.AI
OmniChat AI
Undertow
Localazy
idensys Technologies
Hedy AI
BUSRA GROUP Cabina.AI Cabina.AI OmniChat AI OmniChat AI Undertow Undertow Localazy Localazy idensys Technologies idensys Technologies Hedy AI Hedy AI BUSRA GROUP BUSRA GROUP Robotics (2.4k total votes, 1.3k startups) Robotics Winner: Hidonix Winner: Hidonix Hidonix MedGos
Vitality Robotics MedGos MedGos Vitality Robotics Vitality Robotics Honorable mentions: Honorable mentions: DRONEQUBE
Formic
CENTO software
HealingHand Tech
Vas MedTech
C2Dx, Inc.
Control One DRONEQUBE DRONEQUBE Formic Formic CENTO software CENTO software HealingHand Tech HealingHand Tech Vas MedTech Vas MedTech C2Dx, Inc. C2Dx, Inc. Control One Control One Chatbots (200 total votes, 189 startups) Chatbots Winner: Paidia Gaming Winner: Paidia Gaming Paidia Gaming Datazo InfoTech
Cognitiev Datazo InfoTech Datazo InfoTech Cognitiev Cognitiev Honorable mentions: Honorable mentions: CloudEngine Labs
Brainy Neurals - AI Development Company
iSmart Apps - Oracle Cloud Experts
Link Bell Pvt Ltd
Dicken Media1
Daamtu, AI & Chatbots Solutions
Four Africa CloudEngine Labs CloudEngine Labs Brainy Neurals - AI Development Company Brainy Neurals - AI Development Company iSmart Apps - Oracle Cloud Experts iSmart Apps - Oracle Cloud Experts Link Bell Pvt Ltd Link Bell Pvt Ltd Dicken Media1 Dicken Media1 Daamtu, AI & Chatbots Solutions Daamtu, AI & Chatbots Solutions Four Africa Four Africa Congratulations to you all! We will contact you with details on how to claim your winnings! Congratulations to you all! We will contact you with details on how to claim your winnings! Congratulations to you all! We will contact you with details on how to claim your winnings! See the global regional announcements here.
See the global industry announcements here. See the global regional announcements here.
See the global industry announcements here. See the global regional announcements here. here See the global industry announcements here. here About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries participated in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many storieshave been written about these daring and rising startups. Startups of The Year 2024 many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview Evergreen Tech Company News Visit our FAQ page to learn more. FAQ Download our design assets here. here Check out the Startups of The Year Merch Shop here. here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated packages to solve your marketing challenges. Book a meeting with us to learn more! curated packages Book a meeting with us to learn more! Meet our sponsors: Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool.Get your offer now! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free. Hubspot: Get started for free Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform

Startups of The Year 2024 Winners: AI Industry 

Startups van die Jaar 2024 Winnaars: AI-bedryf

২০২৪ সালের স্টার্টআপ বিজয়ী: এআই শিল্প

Startupe godine 2024 Pobjednici: AI industrija

Las startups del año 2024 ganadoras: la industria de la IA

Vuoden 2024 voittajat: AI-teollisuus

Startupovi godine 2024 pobjednici: AI industrija

Startups of the Year 2024 Winners: AI Industry

2024 жылы Қазақстан индустриясы:

2024-ийн Startups Шагнагч: AI аж үйлдвэрийн

Startupy Roku 2024 Zwycięzcy: Przemysł AI

2024 වර්ෂයේ Startups ජයග්රාහකයින්: AI කර්මාන්තය

Ang mga nag-aalok ng Startups ng Taon 2024: AI Industry

Innovation Has No Boundaries — Meet the Champion Industries of Startups of The Year 2024

الابتكار لا تحتوي على الحدود - تعاقدت مع الصناعات الفاخرة للشركات الناشئة في عام 2024

Інновацыі не маюць межаў — знаёмства з чэмпіёнамі прамысловасці стартапаў 2024 года

Η καινοτομία δεν έχει σύνορα – Γνωρίστε τις πρωτοπόρες βιομηχανίες των νεοσύστατων επιχειρήσεων του 2024

La innovación no tiene fronteras - Conoce las industrias campeonas de las startups del año 2024

नवाचार कोई सीमा नहीं है - वर्ष 2024 के स्टार्टअप चैंपियन उद्योगों से मिलें

イノベーションには国境がない―2024年のスタートアップのチャンピオン産業に出会う

Иновациите немаат граници – Запознајте ги шампионските индустрии на стартапи во 2024 година

यो बर्ष महानगरको अभियान — सम्पदा संरक्षण तथा सम्बर्धन, पर्यटन प्रवर्धनका लागि पूर्वाधार Next Post

Инновации не имеют границ — познакомьтесь с чемпионскими отраслями стартапов 2024 года

Иновације немају границе – упознајте шампионске индустрије стартапа 2024. године

Innovation haina mipaka - Kukutana na viwanda vya kushinda ya Startups ya Mwaka 2024

创新没有界限 - 满足2024年初创企业冠军行业

Messaging & Communications, Media - October 11, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Messaging & Communications startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Messaging & Communications industry. https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in Messaging & Communications here. The Startups in the Messaging & Communications industry nominated for Startups of The Year 2024 include: Intellico Inc
INNZPIRA
firsthub.in
Kitchenara
Creart Digital Media
The Merchant Hub
IPAGE #GrowSmartly
GPS ROTAS SEGURAS
PLATMA
Mission Possible
Fast Remote Services
Accredify
Sconto
Corbin Technology Solutions Private Limited
Evidoo
KUENHA
Megasight
Didimi
Forescribe
ADV Today
NAYAMAX
SODA.Auto
In Plain English
UTech
COOCO
textomap
LEGIONWEB
LogicNimbus Private Limited
Hoags Technologies
JobTab “We are thrilled to recognize the top startups in the Messaging & Communications industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st, and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in Messaging & Communications here. About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. Visit our FAQ page to learn more. Download our design assets here. Check out the Startups of The Year Merch Shop here. HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool. Get your offer now! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free. Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Messaging & Communications, Media - October 11, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Messaging & Communications startup ecosystem. Messaging & Communications, Media - October 11, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Messaging & Communications startup ecosystem. Messaging & Communications, Media - October 11, 2024 Messaging & Communications, Media - October 11, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “ Startups of The Year ” award, featuring the most promising and innovative companies in the Startups of The Year startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Messaging & Communications industry. https://youtu.be/XOpG6B4AKPU?embedable=true https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in Messaging & Communications here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in Messaging & Communications here . here Startup of The Year in Startup of The Year in Messaging & Communications here here The Startups in the Messaging & Communications industry nominated for Startups of The Year 2024 include: Startups in the Startups in the Startups in the Messaging & Communications industry Messaging & Communications industry nominated Intellico Inc INNZPIRA firsthub.in Kitchenara Creart Digital Media The Merchant Hub IPAGE #GrowSmartly GPS ROTAS SEGURAS PLATMA Mission Possible Fast Remote Services Accredify Sconto Corbin Technology Solutions Private Limited Evidoo KUENHA Megasight Didimi Forescribe ADV Today NAYAMAX SODA.Auto In Plain English UTech COOCO textomap LEGIONWEB LogicNimbus Private Limited Hoags Technologies JobTab Intellico Inc INNZPIRA firsthub.in Kitchenara Creart Digital Media The Merchant Hub IPAGE #GrowSmartly GPS ROTAS SEGURAS PLATMA Mission Possible Fast Remote Services Accredify Sconto Corbin Technology Solutions Private Limited Evidoo KUENHA Megasight Didimi Forescribe ADV Today NAYAMAX SODA.Auto In Plain English UTech COOCO textomap LEGIONWEB LogicNimbus Private Limited Hoags Technologies JobTab “We are thrilled to recognize the top startups in the Messaging & Communications industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the Messaging & Communications industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO . “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” David Smooke, HackerNoon Founder & CEO Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st , and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Startups of The Year 2024 nominate their favorite startups until October 31st nominate their favorite startups Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. get free interviews startup-friendly packages startup-friendly packages Evergreen Tech Company News Evergreen Tech Company News In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in Messaging & Communications here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in Messaging & Communications here . here Startup of The Year in Startup of The Year in Messaging & Communications here here About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. Startups of The Year 2024 Startups of The Year 2024 many stories many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview on HackerNoon Evergreen Tech Company News Evergreen Tech Company News Visit our FAQ page to learn more. FAQ FAQ Download our design assets here . here here Check out the Startups of The Year Merch Shop here . here here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. startup-friendly packages startup-friendly packages Meet our sponsors: Meet our sponsors: Meet our sponsors: Wellfound: Join the #1 global, startup-focused community . At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months , to build and scale your company with one powerful tool. Get your offer now ! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free . Hubspot: Get started for free Get started for free Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection , businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform AI end-to-end Search and Discovery Platform

Startups of the Year 2024: 8,350 Startups Nominated in the Messaging & Communications Industry

174 AI Tools To Try

AI Chatbot Helps Manage Telegram Communities Like a Pro

يساعد برنامج الدردشة الآلي AI Chatbot في إدارة مجتمعات Telegram مثل المحترفين

Un chatbot con inteligencia artificial ayuda a gestionar comunidades de Telegram como un profesional

AI Chatbot axuda a xestionar as comunidades de Telegram como un profesional

Il chatbot AI aiuta a gestire le community di Telegram come un professionista

AI チャットボットが Telegram コミュニティをプロのように管理

AI Chatbot Telegram жамааттарын Pro сыяктуу башкарууга жардам берет

AI Chatbot Esalisaka na Gérer ba Communautés ya Telegramme Lokola Pro

AI Chatbot Membantu Mengurus Komuniti Telegram Seperti Pro

AI Chatbot helpt Telegram-communities als een pro te beheren

AI Chatbot ndihmon në menaxhimin e komuniteteve të Telegramit si një profesionist

AI Chatbot ช่วยจัดการชุมชน Telegram ได้อย่างมืออาชีพ

I-AI Chatbot inceda ukulawula uluntu lweTelegram njengePro

Meet Bond and ReactiveKit Mobile app consumers have raised the bar for their expectations while scrolling through an app. Nowadays, everyone wants to see smooth transitions, pixel-perfect apps, and fewer steps. Even a small visual distraction can make the user delete your app. In other words, . your app has to be perfect How do you handle your data changes? There is also another important thing, and that is . I have met tons of apps with poor handling of data changes. For example, you are pulling to refresh the table view content and suddenly the whole content disappears and reappears after 2–3 seconds. In most cases, you are getting the same results back as before the "pull to refresh", so nothing has really changed. Sounds familiar? how you handle the data changes to the UI Let's avoid this kind of situations, and handle data changes properly by using . 👇 bindings and reactive data sources Reactive Programming For those who aren't familiar with the term, reactive is an asynchronous programming paradigm concerned with and the propagation of change. For example, all changes to the model will be automatically reflected in the associated view. 📡 programming data streams If you are interested to find out more about reactive programming click here . Bind with Bond is a binding framework that takes binding concepts to a whole new level. It's simple, powerful, type-safe and multi-paradigm - just like Swift. It simplifies state changes by using bindings and reactive data sources. Bond Swift This library is in my all-time favorites. You can attach it to any component that you like. I will show you how to use Bond with few examples, so you can get the idea of how it's working. Installation For the installation, I am using . I highly suggest that you do the same. Just add the below code in your Podfile and run .👇 CocoaPods pod install target 'YOUR_TARGET' do use_frameworks! pod 'Bond', '~> 6.4.3' end I'm using the latest version of the framework from the day I wrote this post. For version changes, please check here . Add to the top of your class so you can use all the Bond methods. import Bond _Many iOS apps use Google Maps. This is a very common feature, so I have decided to prepare an ultimate guide on Google…_theappspace.com Google Maps SDK for iOS using Swift 4 - The App Space Events I will start by showing you how to get rid of the annoying process of and use the simplified approach from Bond instead. IBAction _ = yourButton.reactive.tap.observeNext { print("Button tapped.") } This will observe your button tap. It listens to because it's the most frequently used event. If you want to handle other events you can use: touchUpInside yourButton.reactive.controlEvents(.touchUpInside).observeNext { e inprint("Button tapped.")} Another example would be observing the text changes in a . Knowing that there is no native approach to this situation, Bond provides us with a simple solution. UITextField _ = yourTextField.reactive.text.observeNext { text inprint(text!)} Now, let me show you a simple binding of the typed text into a . The text will get transformed by using the closure and propagated to the label. is the typed string, so you can add any string transformation that you need. UILabel .map $0 yourTextField.reactive.text.map{ $0?.capitalized }.bind(to: yourLabel) Or, you can use the above example but provide a condition instead. Let's say you need to change the button enabled state as someone types in the text field. txtField.reactive.text.map { $0!.characters.count != 0 }.bind(to: yourButton.reactive.isEnabled) Observable Observables are signals and a typealias for the ReactiveKit type. Whenever the state of the changes, an observer will be notified. Property Observable let animal = Observable("Dog") animal.observeNext { value inprint("Hi \(value)!")} If you can see from the example, whenever the animal observable changes its value an observer will be triggered. To change the value just call . To bind an Observable with a UI component just use . animal.value="Cat" animal.bind(to: yourLabel) Bond also supports two-way binding by using . It means that if the view value changes, it will update the Observable value and vice versa. bidirectionalBind animal.bidirectionalBind(to: animalTextField.reactive.text) _This tutorial is about Instagram API Authentication using Swift and will teach you how to retrieve the ACCESS_TOKEN…_theappspace.com Instagram API Authentication using Swift - The App Space Reactive Data Sources By using reactive data sources, it allows us to easily observe changes in a table or collection view. That means whenever the array changes, the data source methods will update automatically. No need of adding on each array change, and it will update only the changes that were made. 🤘🤘🤘 reloadData() We need to use or that will observe for changes and pass the changes automatically to the data source methods. MutableObservableArray ObservableArray let array = MutableObservableArray([“John”,”Michael”,”Steven”]) I will now present you how easy and short it is to implement the data source of a table view. You don't need to connect the UITableViewDataSource with the table view, as Bond handles that for us. The mandatory and , are "packed" under the array method. In the closure, you can add your own cell logic. See the example below. 👇 numberOfRowsInSection() cellForRowAtIndexPath() bind() array.bind(to: tableView, animated: true) { dataSource, indexPath, tableView in let cell = UITableViewCell(style: .subtitle, reuseIdentifier: “cell”) cell.textLabel?.text = dataSource[indexPath.row] return cell } Now, let's say that the array needs to be updated. At this point, we need to , and forget about the table view and whether it's going to update or not. only focus on the array Here are some methods that you can use to make changes to the array. array.append("Brad") /* appends array with a new object */ array.insert("Brad", at: 2) /* inserts new object at the given index */ array.replace(with: [“John”,"Brad",”Michael”,”Steven”], performDiff: true) /* replaces the array but updates only rows that weren't present in the previous array (in our case index 1) */ array.moveItem(from: 1, to: 2) /* items in array will change places */ array.remove(at: 2) /* removes an item from the array */ array[1] = "David" /* replaces the value at the given index */ By using these methods properly, we provide the best user experience possible. The data will be updated, and the user won't get distracted in any way. I have presented just a few of the many features that Bond offers. Binding and the reactive paradigm can bring your app to the next level, so I would strongly suggest using this approach. If you want to spread the message, please don't forget to 👏 or share this story. Thank you for your attention! 🚀 Check out my latest project: _This app is only available on the App Store for iOS devices. Increase your profits by following our professional BET…_apple.co ‎VIP Sports Bet Tips & Scores on the App Store Read more of my writing on Medium: _Forget MVC, now!_hackernoon.com Introducing Clean Swift Architecture (VIP) _Many iOS apps use Google Maps. This is a very common feature, so I have decided to prepare an ultimate guide on the…_medium.freecodecamp.org Your ultimate guide to the Google Maps SDK on iOS, using Swift 4 _Custom UIView with XIB file is a very common practice in iOS Development. Custom UIView classes don’t contain XIB files…_medium.com SWIFT — Custom UIView with XIB file _A Swift tutorial that will make your app available in Spotlight search_hackernoon.com How to add Spotlight support to your iOS app _Understanding One-to-One and One-To-Many relationships_hackernoon.com Core Data Relationships _All you need to know about Auto Layout_hackernoon.com Understanding Auto Layout in Xcode 9 Subscribe to my Newsletter:

Reactive Programming and Binding in Swift

In retrieval-augmented generation (RAG) pipelines, input efficiency is paramount, not just in terms of tokens, but also character limits When building a multilingual embedding pipeline, I faced a real challenge:the Cohere multilingual model imposes a maximum of 2048 characters not a token limit per input. This article walks you through a clever solution: preprocessing Markdown tables into dense JSON blocks using pymtd2json, to ensure smooth, efficient embeddings without errors. pymtd2json The Challenge: Character Limits vs Token Limits Classical chunking methods, like SentenceSplitter from LlamaIndex, are token-focused: you set a maximum number of tokens per chunk — but not characters SentenceSplitter Why This Matters: Markdown (especially GitHub-Flavored Markdown, GFM) wastes spacewith formatting.
A Markdown chunk might have only 170 tokens but still exceed 2048 characters
This results in rejected API requests or inefficient extra splitting. Markdown (especially GitHub-Flavored Markdown, GFM) wastes spacewith formatting. A Markdown chunk might have only 170 tokens but still exceed 2048 characters This results in rejected API requests or inefficient extra splitting. Important Note: Markdown tables are up to 3x less token-efficient than other formats, further compounding the problem.👉 Read more on token inefficiency of Markdown tables here. Important Note 3x less token-efficient Read more on token inefficiency of Markdown tables here. A Real-World Example: Measuring the Problem Let's dive into a simple simulation: Step 1: Create a Large Markdown Table import pandas as pd

# Build data
data = {
    "Name": [f"Person{i}" for i in range(30)],
    "Age": [20 + i for i in range(30)],
    "City": [f"City{i}" for i in range(30)]
}

# Create DataFrame
df = pd.DataFrame(data)
df.columns = ["A very long row content, which leads to a lot of white spaces", "Age", "City"]

# Convert to Markdown
table_text = df.to_markdown(index=False)
print(table_text) import pandas as pd

# Build data
data = {
    "Name": [f"Person{i}" for i in range(30)],
    "Age": [20 + i for i in range(30)],
    "City": [f"City{i}" for i in range(30)]
}

# Create DataFrame
df = pd.DataFrame(data)
df.columns = ["A very long row content, which leads to a lot of white spaces", "Age", "City"]

# Convert to Markdown
table_text = df.to_markdown(index=False)
print(table_text) This generates a verbose table with 30 rows and a very long header. Step 2: Analyze Token and Character Counts Using Cohere’s tokenizer (available via Hugging Face): from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("Cohere/Cohere-embed-multilingual-v3.0")
encoded = tokenizer(table_text, return_tensors="pt", add_special_tokens=False)

num_tokens = encoded.input_ids.shape[-1]
num_chars = len(table_text)

print(f"Characters: {num_chars}")
print(f"Tokens: {num_tokens}") from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("Cohere/Cohere-embed-multilingual-v3.0")
encoded = tokenizer(table_text, return_tensors="pt", add_special_tokens=False)

num_tokens = encoded.input_ids.shape[-1]
num_chars = len(table_text)

print(f"Characters: {num_chars}")
print(f"Tokens: {num_tokens}") Result: Result: Characters: 2719
Tokens: 432 Characters: 2719 2719 Tokens: 432 432 ⚡ Problem: While token count is fine, character count exceeds 2048, causing API errors like: Problem cohere.error.CohereAPIError: input text exceeds maximum allowed size of 2048 characters cohere.error.CohereAPIError: input text exceeds maximum allowed size of 2048 characters The Solution: Minifying Tables into JSON Instead of traditional Markdown, why not store the data in a dense JSON block? dense JSON block Benefits of Minifying Tables: Remove pipes, dashes, and whitespace, all formatting overhead.
Preserve semantic meaning.
Shrink text to meet character limits safely. Remove pipes, dashes, and whitespace, all formatting overhead. Preserve semantic meaning. Shrink text to meet character limits safely. Example of the compact JSON: {"Name":["Person0","Person1","Person2",...],"Age":["20","21","22",...],"City":["City0","City1","City2",...]} {"Name":["Person0","Person1","Person2",...],"Age":["20","21","22",...],"City":["City0","City1","City2",...]} New Stats: New Stats: Characters: 1027
Tokens: 461 Characters: 1027 1027 Tokens: 461 461 ✅ Now well within Cohere’s input limit! Applying Minification in Practice Want to prepare documents before chunking? Here's how you can automatically process all Markdown files: from pathlib import Path
from llama_index import SimpleDirectoryReader
from your_minifier import MinifyMDT

source_dir = Path("example_dir", "markdown")

documents = SimpleDirectoryReader(source_dir, required_exts=[".md"], recursive=True).load_data()

doc_texts = []
for idx, doc in enumerate(documents):
    doc_texts.append(MinifyMDT(doc.text_resource.text).transform()) from pathlib import Path
from llama_index import SimpleDirectoryReader
from your_minifier import MinifyMDT

source_dir = Path("example_dir", "markdown")

documents = SimpleDirectoryReader(source_dir, required_exts=[".md"], recursive=True).load_data()

doc_texts = []
for idx, doc in enumerate(documents):
    doc_texts.append(MinifyMDT(doc.text_resource.text).transform()) 👉 And voilà: Your data is compact, clean, and embedding-ready! Your data is compact, clean, and embedding-ready! Final Thoughts Working with multilingual RAG systems means optimizing every byte. Whitespace-heavy Markdown tables might look nice for humans, but they’re expensive for machine understanding. By minifying your tables with pymtd2json, you: pymtd2json Cut down API errors.
Reduce token overhead.
Boost overall performance. Cut down API errors. Reduce token overhead. Boost overall performance. Efficiency isn't optional, it's a superpower. 🚀 Efficiency isn't optional, it's a superpower.

AI Fails Over Tables? Stop Using Markdown and Start Minifying

Large Language Models are incredibly powerful and it’s impressive that they have been trained on a vast data corpora. However, how many of us, as we embark on our Founder journey, have the budget to train these models in-house? Likely, very few. But wait, are these pre-trained LLMs helpful to us? Of course, if they are open source. Fortunately, quite a few are available now. So, how exactly are they helpful? Most of us in the AI field are aware of RAGs or have at least heard of them. Let me provide a simple one-line definition. Retrieval-augmented generation is exactly what it sounds like - it retrieves data from the external sources we provide and augments it to the LLM output. It’s extremely useful because it leverages the generative power of LLMs while incorporating the knowledge we supply externally to generate outputs from the desired corpus. If you have a limited external corpus, we can let the model fall back on the general knowledge of the LLM. I am particularly interested in how we eat and deeply believe in the concept of  “garbage in, garbage out” when it comes to food and bodies. If we nourish ourselves with naturally healthy foods, we reflect nature - strong, vibrant, and unstoppable. But if we consume artificial, lifeless foods, we begin to look and feel the same - drained and unnatural. One of the worst consequences of excess artificial and refined food consumption today is diabetes. And who truly understands the real pain points of living with diabetes? It’s simple - the people who experience it firsthand. Given my interest in sourcing experiential data on diabetes using LLMs, I conducted this experiment with Ollama - one of many open-source LLMs that can be utilized for such tasks. I am sharing my notebook step by step with an explanation at each stage. Additionally, to aid comprehension, I am including a high-level architecture diagram. Step 1: Fetch and process content from multiple URLs. We scrape text from the provided list of Reddit URLs and store it in all_texts. Step 1: Fetch and process content from multiple URLs. We scrape text from the provided list of Reddit URLs and store it in all_texts. # Import necessary libraries
import requests
from bs4 import BeautifulSoup
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings import OllamaEmbeddings
from langchain.vectorstores import FAISS
from langchain.chains import RetrievalQA
from langchain.prompts import PromptTemplate
from langchain.llms import Ollama

# List of URLs to scrape
urls = [
    'https://www.reddit.com/r/diabetes/comments/1broigp/what_are_your_biggest_frustrations_with_diabetes/',
    'https://www.reddit.com/r/diabetes_t2/comments/156znkx/whats_the_most_challenging_part_about_dealing/',
    'https://www.reddit.com/r/diabetes/comments/qcsgji/what_is_the_hardest_part_about_managing_diabetes/',
    'https://www.reddit.com/r/diabetes_t1/comments/1hdlipr/diabetes_and_pain/',
    'https://www.reddit.com/r/diabetes/comments/ww6mrj/what_does_diabetic_nerve_pain_feel_like/',
    'https://www.reddit.com/r/AskReddit/comments/avl1x0/diabetics_of_reddit_what_is_your_experience_of/',
    'https://www.reddit.com/r/diabetes_t2/comments/1jggxi9/my_fathers_sugar_levels_are_not_dropping/',
    'https://www.reddit.com/r/diabetes_t2/comments/1jglmie/shaky_feeling/',
    'https://www.reddit.com/r/diabetes_t2/comments/1jgccvo/rant_from_a_depressedeating_disordered_diabetic/'
]

# Initialize text storage
all_texts = []

# Step 1: Fetch and process content from multiple URLs
for url in urls:
    response = requests.get(url)
    soup = BeautifulSoup(response.text, 'html.parser')

    # Extract text from <p> tags
    text = ' '.join([para.get_text() for para in soup.find_all('p')])
    
    if text:  # Store only if text is found
        all_texts.append(text) # Import necessary libraries
import requests
from bs4 import BeautifulSoup
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings import OllamaEmbeddings
from langchain.vectorstores import FAISS
from langchain.chains import RetrievalQA
from langchain.prompts import PromptTemplate
from langchain.llms import Ollama

# List of URLs to scrape
urls = [
    'https://www.reddit.com/r/diabetes/comments/1broigp/what_are_your_biggest_frustrations_with_diabetes/',
    'https://www.reddit.com/r/diabetes_t2/comments/156znkx/whats_the_most_challenging_part_about_dealing/',
    'https://www.reddit.com/r/diabetes/comments/qcsgji/what_is_the_hardest_part_about_managing_diabetes/',
    'https://www.reddit.com/r/diabetes_t1/comments/1hdlipr/diabetes_and_pain/',
    'https://www.reddit.com/r/diabetes/comments/ww6mrj/what_does_diabetic_nerve_pain_feel_like/',
    'https://www.reddit.com/r/AskReddit/comments/avl1x0/diabetics_of_reddit_what_is_your_experience_of/',
    'https://www.reddit.com/r/diabetes_t2/comments/1jggxi9/my_fathers_sugar_levels_are_not_dropping/',
    'https://www.reddit.com/r/diabetes_t2/comments/1jglmie/shaky_feeling/',
    'https://www.reddit.com/r/diabetes_t2/comments/1jgccvo/rant_from_a_depressedeating_disordered_diabetic/'
]

# Initialize text storage
all_texts = []

# Step 1: Fetch and process content from multiple URLs
for url in urls:
    response = requests.get(url)
    soup = BeautifulSoup(response.text, 'html.parser')

    # Extract text from <p> tags
    text = ' '.join([para.get_text() for para in soup.find_all('p')])
    
    if text:  # Store only if text is found
        all_texts.append(text) Step 2: We split the scraped text into more manageable chunks for efficient text processing. We can also reduce memory usage and improve search performance. Step 2: We split the scraped text into more manageable chunks for efficient text processing. We can also reduce memory usage and improve search performance. # Step 2: Split all content into chunks
text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
all_chunks = []
for text in all_texts:
    all_chunks.extend(text_splitter.split_text(text)) # Step 2: Split all content into chunks
text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
all_chunks = []
for text in all_texts:
    all_chunks.extend(text_splitter.split_text(text)) Step 3: We initialize Ollama embeddings. Embeddings are numerical (vector) representations of raw text capturing the semantic meaning of the text. Embeddings enable various ML models process and understand text effectively. OllamaEmbeddings class leverages llama2 model to generate these embeddings. Step 3: We initialize Ollama embeddings. Embeddings are numerical (vector) representations of raw text capturing the semantic meaning of the text. Embeddings enable various ML models process and understand text effectively. OllamaEmbeddings class leverages llama2 model to generate these embeddings. # Step 3: Initialize Ollama embeddings
embeddings = OllamaEmbeddings(model="llama2")  # Adjust model name if needed # Step 3: Initialize Ollama embeddings
embeddings = OllamaEmbeddings(model="llama2")  # Adjust model name if needed Step 4: Facebook AI Similarity Search (FAISS) is a library for efficient similarity search and clustering of high-dimensional vectors. The from_texts function converts chunks of texts into vectors (from step 3) and stores them in the FAISS vector store. FAISS helps you find chunks similar to your query by comparing vector distances (cosine, euclidean) in a highly optimized fashion. Step 4: Facebook AI Similarity Search (FAISS) is a library for efficient similarity search and clustering of high-dimensional vectors. The from_texts function converts chunks of texts into vectors (from step 3) and stores them in the FAISS vector store. FAISS helps you find chunks similar to your query by comparing vector distances (cosine, euclidean) in a highly optimized fashion. # Step 4: Create a FAISS vector store using all chunks
vector_store = FAISS.from_texts(all_chunks, embeddings) # Step 4: Create a FAISS vector store using all chunks
vector_store = FAISS.from_texts(all_chunks, embeddings) Step 5: We initialize Ollama LLM, which will generate responses or process queries based on the knowledge stored in embeddings in the FAISS vector store from step 4. Step 5: We initialize Ollama LLM, which will generate responses or process queries based on the knowledge stored in embeddings in the FAISS vector store from step 4. # Step 5: Initialize the Ollama LLM
llm = Ollama(model="llama2", temperature=0.3) # Step 5: Initialize the Ollama LLM
llm = Ollama(model="llama2", temperature=0.3) Together, steps 3-5 enable RAG, where the LLM can pull knowledge from stored chunks in the vector store and use the retrieved context to  answer a user’s query in the most relevant way. Step 6: Here, we define the ask_question_with_fallback function to query the stored knowledge to answer a user’s query. But if it can’t find similar docs or the similarity score is low, it will fall back to the general knowledge of the underlying LLM (Ollama here). Step 6: Here, we define the ask_question_with_fallback function to query the stored knowledge to answer a user’s query. But if it can’t find similar docs or the similarity score is low, it will fall back to the general knowledge of the underlying LLM (Ollama here). # Step 6: Create the question-answering function
def ask_question_with_fallback(query):
    # Retrieve relevant documents
    docs = vector_store.similarity_search(query, k=3)

    docs = vector_store.similarity_search(query, k=3)
    for doc in docs:
        print(f"Retrieved doc: {doc.page_content[:200]}")
    
    # If no relevant documents or low similarity, use general knowledge
    #if not docs or all(doc.metadata.get('score', 1.0) < 0.3 for doc in docs):
    #    return use_general_knowledge(query)

    if not docs:
        return use_general_knowledge(query)

    # Format retrieved documents as context
    context = "\n\n".join([doc.page_content for doc in docs])
    
    # Construct RAG prompt
    rag_prompt = f"""
    Use the following pieces of context to answer the question at the end. 
    If you don't know the answer based on this context, respond with "NO_ANSWER_FOUND".

    Context:
    {context}

    Question: {query}

    Provide a direct and concise answer to the question based only on the context above:
    """
    
    rag_answer = llm(rag_prompt)
    
    # Check for fallback trigger
    if "NO_ANSWER_FOUND" in rag_answer or "don't know" in rag_answer.lower() or "cannot find" in rag_answer.lower():
        return use_general_knowledge(query)
    
    return {
        "answer": rag_answer,
        "source": "URL content",
        "source_documents": docs
    } # Step 6: Create the question-answering function
def ask_question_with_fallback(query):
    # Retrieve relevant documents
    docs = vector_store.similarity_search(query, k=3)

    docs = vector_store.similarity_search(query, k=3)
    for doc in docs:
        print(f"Retrieved doc: {doc.page_content[:200]}")
    
    # If no relevant documents or low similarity, use general knowledge
    #if not docs or all(doc.metadata.get('score', 1.0) < 0.3 for doc in docs):
    #    return use_general_knowledge(query)

    if not docs:
        return use_general_knowledge(query)

    # Format retrieved documents as context
    context = "\n\n".join([doc.page_content for doc in docs])
    
    # Construct RAG prompt
    rag_prompt = f"""
    Use the following pieces of context to answer the question at the end. 
    If you don't know the answer based on this context, respond with "NO_ANSWER_FOUND".

    Context:
    {context}

    Question: {query}

    Provide a direct and concise answer to the question based only on the context above:
    """
    
    rag_answer = llm(rag_prompt)
    
    # Check for fallback trigger
    if "NO_ANSWER_FOUND" in rag_answer or "don't know" in rag_answer.lower() or "cannot find" in rag_answer.lower():
        return use_general_knowledge(query)
    
    return {
        "answer": rag_answer,
        "source": "URL content",
        "source_documents": docs
    } Step 7: This is the fallback function. If no relevant documents could be retrieved in step 6, the LLM uses its general knowledge to answer the user’s query. Step 7: This is the fallback function. If no relevant documents could be retrieved in step 6, the LLM uses its general knowledge to answer the user’s query. # Step 7: Define fallback general knowledge function
def use_general_knowledge(query):
    general_prompt = f"""
    Answer this question using your general knowledge: {query}
    
    Provide a direct and helpful response. If you don't know, simply say so.
    """
    
    general_answer = llm(general_prompt)
    
    return {
        "answer": general_answer,
        "source": "General knowledge",
        "source_documents": []
    } # Step 7: Define fallback general knowledge function
def use_general_knowledge(query):
    general_prompt = f"""
    Answer this question using your general knowledge: {query}
    
    Provide a direct and helpful response. If you don't know, simply say so.
    """
    
    general_answer = llm(general_prompt)
    
    return {
        "answer": general_answer,
        "source": "General knowledge",
        "source_documents": []
    } Step 8: This step shows an example of how to use this RAG mechanism. You provide a query to the model, and LLM uses external or internal knowledge to answer your query. Step 8: This step shows an example of how to use this RAG mechanism. You provide a query to the model, and LLM uses external or internal knowledge to answer your query. #Step 8
# Example usage
query = "What is the hardest part about managing diabetes?"  # Replace with your actual question
result = ask_question_with_fallback(query)

# Display results
print("Answer:")
print(result["answer"])
print(f"\nSource: {result['source']}")

if result["source_documents"]:
    print("\nSource Documents:")
    for i, doc in enumerate(result["source_documents"]):
        print(f"Source {i+1}:")
        print(doc.page_content[:200] + "...")  # Print first 200 chars of each source
        print() #Step 8
# Example usage
query = "What is the hardest part about managing diabetes?"  # Replace with your actual question
result = ask_question_with_fallback(query)

# Display results
print("Answer:")
print(result["answer"])
print(f"\nSource: {result['source']}")

if result["source_documents"]:
    print("\nSource Documents:")
    for i, doc in enumerate(result["source_documents"]):
        print(f"Source {i+1}:")
        print(doc.page_content[:200] + "...")  # Print first 200 chars of each source
        print() My output from Step 8 is below. The model uses RAG, which identifies a similar document from the FAISS store and answers my query. My output from Step 8 is below. The model uses RAG, which identifies a similar document from the FAISS store and answers my query. In conclusion, leveraging RAG with URLs is a powerful approach for enhanced knowledge retrieval in diabetes-related queries. By combining real-world insights from community platforms like Reddit on top of open-source LLMs, we can offer personalized and accurate information - after all, who understands it better than those living with it every day? This method is not only cost-effective but also fosters collaboration, ultimately improving support for individuals managing diabetes. As AI continues to evolve, its potential to improve healthcare and well-being remains vast. Feature photo by Suzy Hazelwood: https://www.pexels.com/photo/close-up-photo-of-sugar-cubes-in-glass-jar-2523650/ Feature photo by Suzy Hazelwood: https://www.pexels.com/photo/close-up-photo-of-sugar-cubes-in-glass-jar-2523650/

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