The substrate that runs the company
One agent substrate, two fleets: a seven-agent operational platform for a client, and the system that runs our own portfolio. Same memory, same governance, same uptime discipline.
- specialized agents, one operational fleet
- test cases on the platform runtime
- governed tables, RLS on every one
The problem
Agent demos are easy. An agent that is still correct in month four, after the schema migrated, after the prompt changed, after a human trusted it with something operational, is a different engineering problem. The industry mostly hasn’t solved it because the industry mostly hasn’t had to run one.
We have to. Our own company runs on this substrate.
The system
One architecture, instantiated twice.
The client fleet. Seven specialized agents over an operational data warehouse, spanning recruiting, intelligence, finance, outreach, and federal capture, under an apex orchestrator that sees the whole firm. Each agent has its own cognitive schema and memory. Governance is enforced in the database, not in prompts: agents read through views only, a base-table read is a production error; 94 tables carry row-level security with CI invariants that fail the build if a new table ships without it; every outbound message rides a human approval bound to the exact content hash. An agent that cannot cite a source says “source unavailable” instead of inventing one. That honesty contract is a schema constraint, not a hope. 1,209 test cases gate the runtime.
LLMs advise. Code and humans decide.
Our own operation. The same substrate runs a cognitive runtime with persistent memory and an autonomous PM agent that keeps the portfolio’s books: scheduled digests, drift detection, cited status captures. When its production database needed a live migration, the cutover took 12 minutes of downtime, fail-closed behavior proven on prod before the switch.
Running on your own infrastructure is the only review that cannot be gamed. Every sharp edge in this substrate was found by us depending on it.
Receipts
- Seven-agent operational fleet live, apex orchestrator included (2026-06)
- 1,209 test cases on the platform runtime; 94 governed tables across 4 schemas (2026-07)
- 12-minute live production database migration, fail-closed proven (2026-06)
- Production agentic AI since 2021
What this means for you
A control plane is not a chatbot with tools. It is memory, governance, observability, and a database that enforces the rules when the model has a bad day. We build fleets on the substrate our own company already runs on. You own everything we build.