Teams · Enterprise
Bring every AI session onto one shared context layer
ContextStream gives engineering teams persistent memory, intent-aware search, and dependency intelligence so delivery stays fast as teams scale.
What happens next
- Tell us about your team
Its size, the AI tools you use, and what you need to roll out.
- We follow up by email
With next steps and a recommended rollout structure.
- Start the evaluation
A typical technical evaluation starts in days, not weeks.
Need help with an existing account? Contact support.
Talk to sales
Tell us your team context and rollout goals.
What a team rollout includes.
Security and compliance
SSO/SAML roadmap, tenant isolation, and governance controls for production workflows.
Team workspace control
Role-based access, shared memory, and cross-project visibility for engineering groups.
Implementation support
Priority guidance for rollout, migration planning, and technical enablement. Priority channels for rollout blockers and production issues.
Custom integration path
Guidance for deep MCP workflows and internal platform alignment.
Evidence, not just confidence.
These are measured benchmark results, not customer projections.
- 100.00%
Useful-file Recall@10
A useful file reached the first ten results on independently judged positive queries, in production.
- 98.77%
Best-answer Recall@10
A highest-relevance answer file reached the first ten results on the same pinned-repo benchmark, in production.
- 96%
Agent task success
The same agent and repository passed 23 of 24 tasks with project memory, versus 14 of 24 without it.