New top story on Hacker News: Show HN: Open-source Deep Research across workplace applications

Show HN: Open-source Deep Research across workplace applications
6 by yuhongsun | 1 comments on Hacker News.
I’ve been using deep research on OpenAI and Perplexity and it’s been just amazing at gathering data across a lot of related and chained searches. Just earlier today, I asked “What are some marquee tech companies / hot startups (not including the giants like FAAMG, Samsung, Nvidia etc.)”. It’s a pretty involved question and looking up “marquee tech startups” or "hot tech startups" on Google gave me nothing useful. Deep research on both ChatGPT and Perplexity gave really high quality responses with ChatGPT siding on slightly larger scaleups and Perplexity siding more on up and coming companies. Given how useful AI research agents are across the internet, we decided to build an open-source equivalent for the workplace since a ton of questions at work also cannot be easily resolved with a single search. Onyx supports deep research connected to company applications like Google Drive, Salesforce, Sharepoint, GitHub, Slack, and 30+ others. For example, an engineer may want to know “What’s happening with the verification email failure?” Onyx’s AI agent would first figure out what it needs to answer this question: What is the cause of the failure, what has been done to address it, has this come up before, and what’s the latest status on the issue. The agent would run parallel searches through Confluence, email, Slack, and GitHub to get the answers to these then combine them to build a coherent overview. If the agent finds that there was a technical blocker that will delay the resolution, it will adjust mid-flight and research to get more context on the blocker. Here’s a video demo I recorded: https://www.youtube.com/watch?v=drvC0fWG4hE If you want to get started with the GitHub repo, you can check out our guides at https://docs.onyx.app . Or to play with it without needing to deploy anything, you can go to https://ift.tt/AaRhfXp P.S. There’s a lot of cool technical details behind building a system like this so I’ll continue the conversation in the comments.