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), GitHub, YouTube, LinkedIn, and Amazon. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

Add support for indexing multi-modal research data

u/hgarud suggests building a platform that indexes raw, unstructured, and multi-modal research data to make it easier for AI agents to analyze and generate new hypotheses and experiments.

Original Source

@u/hgarud | 1 pts | 3/9/2026

TL; DR: we built a platform that indexes your wandb projects and past experiments and makes it easy for AI agents to analyze and generate new promising hypotheses and experiments. We built new algorithms to be able to ingest and index raw, unstructured, and multi-modal research data and make it available for AI agents. This makes it easy for AI agents to analyze past experimental data to plan and execute new, high quality and diverse research tasks or experiments towards your project goals. It's free so please check it out (https://www.myluca.ai) and let us know what you think. DMs at open. If people are interested, should we work on a Python SDK so that you can bring your own agents (clawed or otherwise)?

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