Shared memory for CTOs
As a CTO you're standing up AI agents across engineering, support, and operations, and you're discovering that the hard part isn't the models, it's the memory. Every team's agents start cold, re-learning your systems and re-deriving decisions that are already documented somewhere, and nothing one agent learns is available to the next. Left alone, this fragments into a dozen home-grown memory stores, each with its own schema, its own retrieval quality, its own security posture, and its own maintenance burden. That's a governance and cost problem before it's a product one. Glen, shared memory for AI agents, gives your whole organization one durable, org-scoped memory layer through a single MCP tool, so you standardize instead of sprawl.
Glen is a standard remote MCP server, so any agent or tool your teams use, Claude Code, Cursor, internal agents, production automations, connects to the same memory through one tool that retrieves relevant context and records new facts in a single round trip. Instead of each team building and operating its own vector store and write path, you have one managed layer with consistent behavior. An engineering agent's hard-won understanding of a subsystem becomes context a support or ops agent can draw on; institutional knowledge stops dying with each session.
The org-scoped model is what makes this a leadership-grade decision rather than a per-team hack. Memory belongs to the organization: every member's agents read and write the same store, new hires' agents inherit accumulated knowledge automatically, and provenance is tracked so you know which caller wrote what. Access is scoped by organization, authenticated over OAuth 2.1 or API keys, and the security boundary is explicit, your database credentials and auth secret, documented rather than improvised across a dozen side projects. Consolidating on one memory layer means one place to reason about access, retention, and cost instead of an uncontrolled sprawl of bespoke stores. You adopt it once and give every team durable, shared agent memory without each reinventing the infrastructure. For a CTO, Glen is the difference between AI memory as governed infrastructure and AI memory as shadow IT.
FAQ
- How does Glen handle access control across teams?
- Glen is org-scoped: every member of an org can read and write the org's stores, authenticated via OAuth 2.1 or API keys. callerId tracks provenance (who wrote what) so you keep an audit trail without per-user silos.
- What's the security boundary I'm signing up for?
- Memory content is stored in your Postgres with disk-level encryption from your provider and TLS in transit; the documented boundary is your database credentials and the auth secret. It's one consistent posture instead of a dozen improvised ones.