[Launched on Product Hunt today]: Weavable - reliable work context for AI agents
We launched Weavable on Product Hunt today, your persistent context for AI workflows!
If you've built AI workflows on real business data, you've hit this: the output is almost right but not reliable enough to act on. The problem isn't the model. There's no layer tracking cause and effect across your work data over time, so you end up juggling multiple MCPs, cluttering what the agent sees, and burning through tokens to get an answer you can act on.
Weavable is that layer. It sits underneath your tool stack, pre-processes and scopes context from HubSpot, Jira, Slack, Zendesk, Notion and more, and serves it to any agent through a single MCP endpoint.
Things like renewal outreach, pre-meeting briefs, and pipeline summaries you can actually act on. 85% favorable outputs in LLM-as-a-judge evals against baseline retrieval, up to 90% token savings.
Would love feedback from anyone running agents against real business data.
This is a strong category, because the pain is not “better retrieval.” It is whether the agent has enough reliable work context to act without creating risk.
Weavable explains the stitching idea, but it may feel a bit soft for what you’re actually building: a context control layer underneath business agents.
If this becomes infrastructure for reliable agent workflows, a sharper .com like Exirra.com would probably carry the category better. It sounds more like an intelligence/context system than a workflow helper.