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Linkeddit is an AI demand and competitor intelligence platform for SaaS teams, agencies, and founder-led sales. It monitors review sites like G2, Capterra, TrustRadius, and Trustpilot plus the open web, delivering weekly graded competitor briefs covering launches, pricing changes, complaint themes, and switching signals. Its AI-powered lead pipelines find buyers actively looking to switch and draft personalized outreach for each one, while Answer Radar shows where ChatGPT, Perplexity, and Gemini recommend competitors instead of you, then helps you fix it. It was Product Hunt's #1 Product of the Day.
It delivers a weekly graded competitor intelligence brief that surfaces each competitor's moves (launches, pricing changes, partnerships, funding, hiring) and user pain points, each dated, cited, and tied to your product. A live Demand Intelligence feed shows buyer intent and competitor complaints so you can see who is ready to switch. Answer Radar measures where AI answer engines like ChatGPT, Gemini, Perplexity, and Claude recommend competitors instead of you, ranks the gaps, and drafts source-backed fixes.
On top of that, Linkeddit runs AI lead generation pipelines that find buying-intent posts, AI reply drafts, keyword research scored by conversion potential, an AI content writer and CMS for planning and scheduling, and scheduled monitors on a daily, weekly, or monthly cadence. It connects to Claude, Claude Code, Cursor, VS Code, Windsurf, and ChatGPT over MCP.
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Linkeddit's answer
Linkeddit is built as a modern web application with AI at the core. It uses large language models for intent scoring, lead insights, reply drafting, and content generation, a PostgreSQL database, scheduled data pipelines for monitoring reviews, Reddit, and competitor sites, and the Model Context Protocol (MCP) with OAuth 2.1 for integrations with Claude, Cursor, VS Code, Windsurf, and ChatGPT.
Linkeddit's answer
Linkeddit started as a Reddit lead generation tool after its founder kept seeing the same pattern while growing his other products: the best customers were people publicly complaining about a competitor or asking for alternatives, and no affordable tool surfaced those moments reliably. It launched on Product Hunt and became #1 Product of the Day. From there it expanded beyond Reddit into full demand and competitor intelligence, adding review-site mining, weekly competitor briefs, answer engine optimization, and MCP support, all built around the same original insight: the strongest signal in any market is a buyer ready to switch.
Linkeddit's answer
SaaS teams, agencies, consultants, and founder-led sales teams that want to win customers from competitors. Typically these are B2B companies without a dedicated competitive intelligence team who need to know what competitors are doing, who is unhappy with them, and how to reach those buyers first.
Linkeddit's answer
Linkeddit is the only demand and competitor intelligence platform built around one core signal: buyers who are ready to switch. Instead of just monitoring mentions or sending keyword alerts, it reads competitor complaints and buying-intent posts across G2, Capterra, TrustRadius, Trustpilot, Reddit, and the open web, then turns that into scored leads, a weekly graded competitor brief, and content that wins those buyers. It also includes Answer Radar, which measures where AI answer engines like ChatGPT and Perplexity recommend competitors instead of you, and an MCP connector that puts the entire platform inside Claude, Cursor, and other AI assistants.
Linkeddit's answer
Enterprise competitive intelligence suites like Crayon, Klue, and Kompyte are built for large teams with large budgets. Linkeddit delivers the same core value, competitor tracking, switching-intent detection, and weekly briefs, as a self-serve product starting at $49/month. Compared to Reddit-only tools like GummySearch or Syften, Linkeddit goes further: it scores leads by buying intent instead of just alerting on keywords, covers review sites and the open web instead of Reddit alone, and includes a content CMS, keyword research, and MCP integration in one platform. You get warm leads with buying intent, not cold contacts.
Linkeddit's answer
Over 10,000 businesses and solopreneurs use Linkeddit, and customers include B2B SaaS companies, marketing agencies, and independent consultants.
Based on our record, React Native UI Kitten seems to be more popular. It has been mentiond 12 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.
Https://akveo.github.io/react-native-ui-kitten/ is a good alternative, I especially like their demo app, I can just refer a client to that and ask them what screens they like. Source: over 3 years ago
React Native UI Kitten is a React Native implementation of the Eva Design system. It offers a set of general-purpose UI components styled in the same way to take care of visual appearance. There are a lot of standalone components available as well. - Source: dev.to / over 3 years ago
UI Kitten: UI Kitten is a React Native framework for creating stunning cross-platform mobile applications. It is based on Eva Design System and provides a set of general purpose UI components styled in a similar way. - Source: dev.to / almost 4 years ago
In the application we built for the client we had two modal instances, the filtering modal (that used the native modal) and an alert modal (where we used UI Kitten's modal). We like the native modal because it offer's us the possibility of deciding how it transitions and it's easier to set it up fullscreen. - Source: dev.to / over 4 years ago
Image source: https://akveo.github.io/react-native-ui-kitten/ React Native UI Kitten โ a React Native implementation of the Eva Design system. It offers a set of about 20 general-purpose components styled in the same way to take care of visual appearance. There are a lot of standalone components available as well. The library is based on Eva Design System, containing a set of general-purpose UI components styled... - Source: dev.to / over 4 years ago
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