MAYNFRME

The problem

Companies spend millions on AI tools but every interaction starts from zero. There's no canonical memory layer — no place where the company's accumulated context, decisions, projects, and people-knowledge lives in a way every agent and human can use.

Our thesis

The companies that win the next decade will own a memory layer their AI agents query — not a documentation system humans pretend to keep updated.

What it is

MAYNFRME is an AI operating system for the company: project state, agent state, knowledge state, and operator commands — composable, queryable, and owned by the business.

How it's built

• ▸ Next.js + Postgres with pgvector for embedded retrieval
• ▸ Agent runtime supporting OpenAI, Anthropic, and local models
• ▸ Structured event log — every decision becomes part of the memory
• ▸ Composable commands that orchestrate agents across projects, ops, and growth
• ▸ Identity + ACL layer so agents only see what they're authorized to see

Hosting + stack

Vercel + Neon + Cloudflare for embeddings cache. Self-host option for enterprise tier.

Approach

1. Start with the memory model: events, projects, people, artifacts, decisions.
2. Build retrieval before generation. The reasoning is downstream of what the system can recall.
3. Treat agents as composable workers, not chat interfaces.
4. Design for the swap: every model is replaceable behind a single contract.

The goal

Become the canonical operating layer modern companies run their AI on — vendor-agnostic, owned, compounding.