Your AI agents shouldn't have to search for what they need. Dendrite monitors agent context in real-time and proactively injects the institutional knowledge they need — before they ask.
Enterprise knowledge is scattered across dozens of systems. Your agents can't use what they can't find — and they don't know what they don't know.
Retrieval-augmented generation still waits for a query. If your agent frames the question wrong — or doesn't know to ask — RAG returns nothing useful.
Confluence, Notion, Slack, Drive, internal wikis. Critical context is fragmented across systems that don't talk to each other — or to your agents.
Every piece of institutional knowledge your agent doesn't have is an invitation to make something up. The cost isn't just wrong answers — it's lost trust.
Everyone else built better search. We built something fundamentally different.
Ingest institutional knowledge from every source — Confluence, Notion, Slack, Drive, codebases, wikis. One integration layer, total coverage.
Build a living knowledge graph that maps relationships, dependencies, and relevance across your entire organization's institutional memory.
Monitor agent context in real-time. Score relevance against your knowledge graph. Proactively inject exactly what's needed — before the agent asks.
Glean, Notion AI, and every other enterprise knowledge tool starts from the same assumption: the user knows what to ask. That worked for humans. It doesn't work for agents.
AI agents operate at machine speed across thousands of concurrent conversations. They can't pause to craft the perfect search query. They need the right context to show up automatically, weighted by relevance, and injected at exactly the right moment.
That's not search. That's a fundamentally different product. That's Dendrite.
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