The context graph for agentic GTM teams. Unify the data scattered across your GTM tools into one identity-resolved account any agent reads in a single call.
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The context graph for agentic GTM teams. Nous centralizes the data scattered across your GTM tools into one context graph, resolving every person and company into a single record your agents read in one call instead of stitching six tools together and guessing. Open source, with a hosted version.
- Every account in one record. Nous resolves the emails, profiles, and duplicates scattered across your tools into one person or company, so every agent works from the same complete account. - Every fact carries its source. Each detail comes with where it came from and how fresh it is, so an agent acts on what it can trust and you can trace any answer back. - The whole account in one call. An agent reads the full context in a single request instead of stitching six tools together and rebuilding it every time. - Consistent across every agent. The more agents you run, the more this matters. They all read the same context, so the same account returns the same answer. - Trained on your own data. Every reply, meeting, and closed deal feeds back into the graph, sharpening ICP fit on your own outcomes so it gets more accurate over time. - Purpose-built for GTM. Accounts, buying committees, signals, and ICP fit are modeled out of the box, mapped to how GTM teams actually work.
Nous is built on three layers. Every signal from your tools lands as an observation, immutable evidence of something that happened or was said. Observations resolve to entities, one canonical record per person and company. From the evidence on each entity, Nous de
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