patent falcon
We've built a memory layer for LLM apps so conversations stay personalized across sessions.
What it does:
Stores durable user memories (facts, preferences, profile state)
Recalls relevant context automatically before each response
Supports chat history + structured memory operations (create/read/update/search)
Includes claim/profile flows for more reliable long-term context
Built entirely on OpenAI with O-Series via Cerebras + APIs
If you’re building chat apps, assistants, or multi-session workflows, this pattern helps reduce repetitive prompts and improves continuity.
Fully supports OpenAI, Claude & Gemini.
Available via HTTP Endpoints, NPM or Python
Demo/docs: https://mnexium.com/docs
Happy to share any information or answer any questions.
glacial cosmos