Your team's shared knowledge, in every LLM.
Capture what your team knows once. Recall it everywhere — in Claude, ChatGPT, and Gemini — so no one starts from scratch.
Angareion is shared memory and context infrastructure for AI-powered teams. It lets every LLM your team uses — Claude, ChatGPT, Gemini, and others — draw from the same memory store, so knowledge captured in one tool is instantly available in all of them. Teams use Angareion to share institutional knowledge, deploy LLM-agnostic specialists, and ensure every AI answer is traceable back to a source.
Every assistant forgets what the last one learned
Switch from Claude to ChatGPT to Gemini and you start over every time — re-explaining the same context, re-pasting the same background, fumbling with myriad markdown files. Angareion is the shared memory & context layer where your team's knowledge lives, so what one assistant learns is easily captured and recalled by the next.
Angareion ranks memory and knowledge by recency and strength, and hands context off between your sessions today — with hand-off across teammates coming next, so one person's hard-won context becomes the whole team's.
How Angareion works
LLM-agnostic specialists
Scale expert behavior and agentic best-practices across your whole team, without the upkeep
An Angareion specialist draws on the memory and knowledge your team has already captured, grounding its outputs in real, citable context. Define it once and everyone on the team can invoke it from whichever LLM they use, with no per-user setup and no per-tool duplication. The specialist stays current because the knowledge base it draws on stays current.
Drafts product-marketing briefs for feature announcements, drawing on your team’s positioning, messaging pillars, and past launch decisions to produce copy that stays consistent with how your organisation talks about itself.
- Draws on
- team + institutional memory
Specialists that work from institutional knowledge, not their assumptions
Angareion specialists draw on your team’s shared memory, institutional knowledge, established best practices, and ingested external sources — documents, websites, and reference material your team has already brought in. Responses are grounded in that corpus and cite their sources, so you can trace every output back to the information it came from. Specialists can also be configured to produce output in the formats and structures your team actually uses, so the work they generate fits directly into your existing workflows.
Searches external sources — architecture documents, best practices, product briefs, and the web — then stores findings as memories your whole team can draw on.
- Saves to
- team + institutional memory
The more your specialists work, the smarter your whole team gets
Angareion specialists don’t just answer questions, they can research, synthesize findings, extract best-practices, and publish this valuable information back to your shared memory. Every insight a specialist produces is available to every other specialist and team member, so knowledge compounds instead of disappearing into the ether.
Governed knowledge
Every answer your agents produce is traceable
When an agent draws on memory, Angareion records what it used — the source document, the decision it informed, and who verified it. Every response is grounded in citable evidence. When a regulator, an auditor, or a colleague asks what your agents were reasoning from, you have the answer.
Every piece of research is sourced, stored, and attributed
When a specialist or agent does research, Angareion records what it found and where — not just the output, but the citations. Each memory carries its source, the colleague who verified it, and when it was last confirmed current. So when your agents reason from that knowledge, the chain of evidence is intact. Not a confident assertion — a documented fact.
NIST AI RMF Govern 1.7 requires that AI systems maintain records of data provenance, decision rationale, and human oversight events. Audit logs must be immutable and reconstructable for post-incident review.
- Sources
- NIST · CSA · EU AI Act · ISO 42001
- Saved to
- team memory
- Verified by
- Alice · today
Agents reason from verified knowledge, not from assumption
When a teammate or agent asks about compliance, security posture, or best practices, Angareion surfaces what your team has already verified — with citations and a freshness timestamp. Agents don't fabricate an answer from training data. They draw on what your organisation has documented, sourced, and confirmed. When those facts change, the knowledge updates — so every agent drawing on it works from current information.
Based on your team's research and ingested compliance documents, agent deployments must maintain immutable logs of tool calls, data accessed, and decision points.
- Citations
- 3
- Sources
- NIST AI RMF · EU AI Act · team policy
- Last verified
- 2 days ago · Alice
Why Angareion
“An LLM without shared memory is a brilliant new hire with amnesia every morning. Angareion gives every LLM the same memory and context, so your team never re-onboards its tools.”
Cross-LLM portability
The same memory in Claude, ChatGPT, and Gemini — not locked to one runtime.
Team knowledge, not just personal
Institutional knowledge your whole team curates and shares, not a private notepad.
Specialists on the whole corpus
LLM-agnostic expert agents backed by your entire memory, callable from any tool.
Under the hood, memory is multi-modal — combining vector, graph, and full-text retrieval — so the right context surfaces however you ask for it. And every workspace is private to your team — your team's knowledge stays your team's. Angareion works with Claude, ChatGPT, Gemini, Microsoft Copilot, Cursor, GitHub Copilot, and any MCP-compatible runtime — 6+ integrations out of the box.
Frequently asked questions
What is Angareion?
How does Angareion work?
What LLMs does Angareion support?
How is Angareion different from a vector database?
| Vector database | Angareion | |
|---|---|---|
| Scope | Storage primitive | Full lifecycle — ingest, curate, cite, decay |
| Governance | Raw embeddings, no provenance | Citations + source attribution on every record |
| Deployment | API integration required | MCP-native — works in Claude, ChatGPT, Gemini, Cursor out of the box |
Is my team's data private?
What is an LLM-agnostic specialist?
How do I get started with Angareion?
Give your team one memory across every LLM
Angareion is in private beta. Request access and we'll reach out when your spot opens — no credit card, no commitment.