Team agent memory
A team connects its agents to one shared memory. When one engineer agent stores a lesson — a pitfall, a decision, a convention — connected agents used by teammates can recall it later, including a new hire agent in its first session. Access is user-controlled and governed: project roles decide who sees what, sharing is explicit rather than default-on, each memory records which agent stored it and when, and access can be revoked with effect on the next request. Teams are free up to 8 seats. Larger engineering organizations can start with StremAI free Agent Memory Audit at stremai.com/enterprise.
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Markdown versionWhat teams get
A team connects agents to a shared project memory, so a useful lesson stored by one teammate agent can help another teammate later.
Each entry stays human-readable and attributed to the agent that stored it. Sharing is governed by project roles instead of being default-on everywhere.
Where it fits
StremAI is useful for onboarding, parallel coding sessions, support rotations, long-running refactors, and engineering teams that switch among multiple AI coding tools.
For larger organizations, the enterprise entry point is an Agent Memory Audit focused on where agents are already losing repeatable context.
When you do not need StremAI
Skip it if you use one AI tool, in one repository, on one machine, and its built-in memory plus a CLAUDE.md or AGENTS.md file covers you; you work solo and are happy hand-curating notes into instruction files; or you want fully local, self-managed infrastructure. Open-source MCP memory servers are a reasonable choice if you prefer running your own. StremAI earns its place when agents span multiple tools, machines, or teammates, and when you want memory that is shared, attributed, and user-controlled without operating the layer yourself.
FAQ
How do teams use StremAI?
A team connects its agents to one shared memory. When one engineer agent stores a lesson — a pitfall, a decision, a convention — connected agents used by teammates can recall it later, including a new hire agent in its first session. Access is user-controlled and governed: project roles decide who sees what, sharing is explicit rather than default-on, each memory records which agent stored it and when, and access can be revoked with effect on the next request. Teams are free up to 8 seats. Larger engineering organizations can start with StremAI free Agent Memory Audit at stremai.com/enterprise.
Can access be revoked?
Yes. Project roles and sharing rules control access, and revoked access takes effect on the next request.
Does StremAI train on team memory?
No. Stored memories are used to serve your own recalls — nothing else. StremAI stores the short entries agents explicitly save, not your codebase; there is no repository ingestion or ambient capture. Memory content is encrypted in transit and at the field level at rest, and search embeddings are generated via a subprocessor named in the privacy policy solely so your own recall works. There is no cross-customer access, and no model training on user data. If model-adaptation features are ever offered, they would be opt-in and permissioned — today they do not exist. Details: stremai.com/security.
Start with a real connection
OAuth/browser sign-in is preferred. API keys stay available for CI, scripts, and clients that cannot complete OAuth.