This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Repo is a permission-aware context layer that lets AI agents retrieve source-backed company knowledge without dumping everything into a prompt. Connect tools like Slack and Google Drive, with more sources coming, scope what each agent can access, and return context with evidence, freshness, citations, and limitations so agents can answer, draft, or act with receipts.
Hey Product Hunt - I am Gabriel, one of the builders behind Repo.
I started working on Repo because every serious AI agent eventually runs into the same problem: it can sound useful, but it does not reliably know what the company knows, where that knowledge came from, or whether it is allowed to use it.
Repo is our attempt at a company memory layer for agents.
Instead of giving an agent one giant prompt, the agent asks Repo for context. Repo checks scope, searches approved sources, and returns source-backed context with evidence, freshness, citations, and limitations.
We are early and still building in public. The first version focuses on connectors, semantic retrieval, API access, and our Context Contract: the structured response format agents receive when they ask for company context.
The bigger vision is simple: agents should not just answer confidently. They should answer with receipts.
I would love feedback from people building agents, internal tools, support workflows, sales ops, or enterprise AI systems. What context do your agents struggle to access safely today?
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About Repo on Product Hunt
“Company memory for production AI agents”
Repo was submitted on Product Hunt and earned 6 upvotes and 2 comments, placing #34 on the daily leaderboard. Repo is a permission-aware context layer that lets AI agents retrieve source-backed company knowledge without dumping everything into a prompt. Connect tools like Slack and Google Drive, with more sources coming, scope what each agent can access, and return context with evidence, freshness, citations, and limitations so agents can answer, draft, or act with receipts.
Repo was featured in Developer Tools (514k followers) and Artificial Intelligence (471k followers) on Product Hunt. Together, these topics include over 172.2k products, making this a competitive space to launch in.
Who hunted Repo?
Repo was hunted by Gabriel Moseti. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Repo stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Gabriel Moseti