Resources
Build company knowledge people and agents can trust.
Practical guides on retrieval, permissions, organizational memory, deployment, and the operating details behind production-ready AI knowledge.
Documentation
Set up workspaces, connectors, roles, API access, and MCP clients.
EngineeringValidation and benchmarks
Understand how retrieval quality, multimodal needles, ACL isolation, and consistency are measured.
EvaluationCompare your options
Compare the knowledge foundation, AI workspace and operating model for your organization.
Model freedomModels and providers
Choose centrally managed access, BYOK or your own inference without changing your knowledge foundation.
AI at workAgents and automations
Move from direct chat to recurring, permission-controlled work with company context.
Point of viewWhy CogLake
Why organizational knowledge should be treated as durable infrastructure.
Latest thinking
Research and operating lessons.
Knowledge infrastructure
18 Aug 2026 · 7 minWhy enterprise AI needs evidence, not only answers
A useful answer is only the beginning. Enterprise teams also need provenance, permissions, and a path back to the original file.
Read articleRetrieval engineering
11 Aug 2026 · 9 minBeyond basic RAG: building a governed evidence engine
Exact terms, semantic meaning, graph relationships, and corrective retrieval solve different failure modes. The hard part is governing their combination.
Read articleKnowledge continuity
4 Aug 2026 · 6 minWhat happens to company knowledge when people leave?
The most valuable knowledge is often not a document. It is the connection between a decision, a customer, a result, and the person who understood why.
Read article