RequestHunt is a community-driven platform that collects and curates feature requests from X (Twitter), Reddit, and GitHub. We help product teams discover what features real users are asking for, making it easier to validate product ideas and prioritize feature development based on actual user demand.

How does RequestHunt collect feature requests?

RequestHunt uses AI-powered extraction to automatically collect feature requests from social media platforms including X, Reddit, and GitHub. The platform monitors discussions, issues, and posts to identify genuine user feature requests, extracting key information like the requested feature, product mentioned, and user sentiment.

Who uses RequestHunt?

RequestHunt is used by product managers, founders, developers, and product teams who want to discover what features real users are requesting. It's particularly valuable for startups looking to validate ideas, established companies prioritizing their roadmap, and developers building products that solve real user problems.

Is RequestHunt free to use?

Yes, browsing and searching feature requests on RequestHunt is completely free. We also offer API access for developers who want to integrate feature request data into their own applications. Check our pricing page for API plan details.

How often is RequestHunt data updated?

RequestHunt continuously collects feature requests from Reddit, X (Twitter), and GitHub. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

[Clear Match] AI-Powered Chat for Data Discovery and Priority Insights

Create an intelligent chat interface that allows users to discover actionable insights from their Clear Match data using natural language queries. The primary goal is to help users identify high-priority opportunities they might otherwise miss, and a secondary goal is to reduce manual effort in data discovery.

Original Source

@@costajohnt | 0 pts | 7/9/2025

# AI-Powered Chat for Data Discovery and Priority Insights ## Background & Goals Create an intelligent chat interface that helps users discover actionable insights from their Clear Match data through natural language queries. This feature addresses the need for better task prioritization and data discoverability without requiring complex ML model training. **Primary Goal**: Help users identify high-priority opportunities they might otherwise miss **Secondary Goal**: Reduce time spent manually searching through data **Ultimate Business Goal**: Improve candidate placement efficiency and revenue generation ## User Problem Statement Users struggle to prioritize their daily tasks because important insights are buried in data: - Job postings from high-engagement contacts get overlooked - Time-sensitive opportunities expire while working on lower-priority items - Manual data exploration is time-consuming and inconsistent - Users don't know what questions to ask of their data ## User F

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