
NativeBase
React Native
React Native Desktop
React Native UI Kitten
React Native Paper by Callstack
React Native Elements
Flutter
Shoutem
LeadGenRunner
Devi AI
Brand24
DMpro.ai
LeadAny
Lead Cheap
Leado.co
TGDesk
Stop spending hours scrolling through Telegram groups looking for leads. LeadGenRunner does it for you.
LeadGenRunner is an AI-powered tool that monitors Telegram groups and channels for buyer-intent messages matching your keywords. When a potential client posts a message, you get an instant notification with the message content, sender info, and a direct link.
What makes it different:
AI Lead Classification โ A specialized AI agent analyzes every matching message for intent, urgency, and relevance, classifying leads as Hot, Warm, or Cold so you focus on what matters.
AI Reply Suggestions โ Don't know how to start the conversation? AI drafts an engaging, contextual response. Just review and send.
Channel Discovery โ AI finds relevant Telegram groups and channels for your niche automatically, expanding your reach.
Scale Without Hiring โ Monitor 500+ chats simultaneously without additional staff. One person can handle what used to require a team.
Real-Time Analytics โ Track which chats bring the most leads, which keywords perform best, and optimize your strategy with data.
Plans start at $9/month. Free 5-day trial, no credit card required.
Supports English, Russian, Spanish, Portuguese, Turkish, and Arabic.
NativeBase
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LeadGenRunner's answer:
LeadGenRunner is the only tool that combines real-time Telegram group monitoring with AI-powered lead classification. While other tools scrape member lists or require manual searching, LeadGenRunner monitors public messages 24/7 for buyer-intent keywords and uses AI to classify every lead as Hot, Warm, or Cold - so you only focus on prospects ready to buy. It also generates contextual reply suggestions, letting you respond in seconds instead of hours.
LeadGenRunner's answer:
Three reasons: (1) It's Telegram-native - built specifically for Telegram's ecosystem using the official API, not scrapers that risk account bans. (2) AI does the heavy lifting - instead of reading hundreds of messages yourself, AI classifies leads by intent and urgency, and drafts ready-to-send replies. (3) Scale without hiring - one person can monitor 500+ chats simultaneously, replacing what used to require a team of 3-5 people manually scrolling through groups. Plans start at $9/month with a free 5-day trial, no credit card required.
LeadGenRunner's answer:
Digital marketing agencies, B2B sales teams, freelancers, and small business owners who use Telegram as a sales channel. Particularly popular with agencies managing client outreach in Telegram communities, crypto/Web3 projects monitoring industry conversations, real estate professionals tracking buyer inquiries, and consultants looking for project opportunities in niche groups. The common thread: they know their ideal clients are posting in Telegram groups right now, but finding those messages manually is unsustainable.
LeadGenRunner's answer:
LeadGenRunner was born out of frustration. I was spending 3-4 hours every day scrolling through dozens of Telegram groups looking for potential clients - people asking for recommendations, looking for services, discussing problems I could solve. The messages were there, but finding them was like looking for a needle in a haystack. I built a simple keyword monitor for myself, then added AI classification when I realized that even with keyword matches, 70% of messages were noise. The AI layer changed everything - suddenly I was only seeing high-intent leads. I turned it into a product in 2025, and now it saves users hours every day while finding leads they would have otherwise missed.
LeadGenRunner's answer:
LeadGenRunner is a web-based SaaS application built with Python (FastAPI) on the backend and Vue.js on the frontend. It uses the official Telegram API via Pyrogram for real-time message monitoring, OpenAI GPT for AI lead classification and reply generation, and PostgreSQL for data storage. The platform is hosted on cloud infrastructure with real-time WebSocket notifications.
LeadGenRunner's answer:
Based on our record, NativeBase seems to be more popular. It has been mentiond 22 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Gluestack, like any other customizable UI library, is built to make styling less cumbersome. It comprises a set of themed and unstyled components easily integrated across different platforms and devices. Originally, Gluestack was a part of NativeBase, a component library for both React and React Native. With performance and maintainability in mind, NativeBase was split into two parts, focusing on a universal... - Source: dev.to / over 2 years ago
Just like the other libraries mentioned in this article, Gluestack is another unstyled component library. Originally a part of NativeBase, the developer team created this library to prevent bloat and enhance maintainability of the project. - Source: dev.to / almost 3 years ago
KumaUI : Another relatively new contender, Kuma uses zero runtime CSS-in-JS to create headless UI components which allows a lot of flexibility. It was heavily inspired by other zero runtime CSS-in-JS solutions such as PandaCSS, Vanilla Extract, and Linaria, as well as by Styled System, ChakraUI, and Native Base. ### ๏ปฟVue. - Source: dev.to / almost 3 years ago
NativeBase is a collection of essential cross-platform React Native components. The components are built with React Native combined with some JavaScript functionality with customizable properties. NativeBase is fully open-source and has 18,000+ stars on GitHub. - Source: dev.to / over 3 years ago
CSS-based UI libs don't make sense on mobile; your new options include NativeBase, React Native Elements and others). Some web-based UI libs do have RN siblings though - such as React Native Material and React Native Paper (for Material-UI), and tailwind-rn (for Tailwind). This just means new decisions to make, some learning, and new paradigms for how to use the new libs. - Source: dev.to / over 3 years ago
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