AI infrastructure · In development
MAYNFRME®
The memory layer before the agent swarm.
MAYNFRME gives companies a structured memory and agent runtime so AI work can reference decisions, projects, assets, people, and permissions instead of starting from zero.
The problem
Teams buy AI tools, then watch every interaction reset. The company context is still scattered across docs, chats, drives, and human memory.
Our thesis
Useful agents need company memory, tool boundaries, and permissioned context. Model choice matters less than the operating layer the models can safely query.
What it does
MAYNFRME organizes business context into a queryable memory layer and gives agents a controlled runtime for useful work.
System layers
- ▸ Memory model: projects, decisions, artifacts, people, accounts, and operating context.
- ▸ Retrieval layer: search and embeddings grounded in business-owned sources.
- ▸ Agent runtime: tasks, tools, state, logs, and human approval points.
- ▸ Access control: permissions that keep agents inside the right boundaries.
Diagnostic signals
- AI output is generic because the tools do not know the business.
- The same context is pasted into every prompt, every week.
- The team wants agents, but has not built the memory those agents need.
Best fit
Best for teams already using AI heavily enough that context fragmentation is now the constraint.
Next step
See whether MAYNFRME belongs in your operating system.
The paid diagnostic maps the constraint first, then recommends the product layer, custom build, or operating rhythm that actually fits.