The Brain
Persistent operational intelligence for machines and infrastructure.
Built for organizations whose most valuable data can never leave their own walls.
- Status
- Pre-revenue · In validation
- Raising
- $750K · Seed
- Beachhead
- Oil & Gas
- Server
- Built in Rust
What we built
A private language model called The Brain. This AI model is built from scratch by our team and designed for companies that cannot use general-purpose AI due to security and cost.
A model whose cost grows in a straight line rather than a square — with a persistent memory for every tracked entity, running entirely inside the customer’s infrastructure, and small enough to deploy on a device.
The production server is written in Rust, known for performance and memory safety, and is already built and tested.
The problem
Where AI breaks
Why you can’t use ChatGPT or Llama
Standard transformer models get more expensive quadratically as a record gets longer. That’s fine for a chat message. It breaks down when the record is five years of sensor readings on one machine.
Most tools solve this by throwing history away: a short window, a rolling summary, a truncated log. That’s exactly where the pattern that would have predicted the failure gets lost.
Not a private ChatGPT
The Brain gives every tracked entity — a pump, a vehicle, a server — its own persistent memory that accumulates over its lifetime instead of starting from nothing every session.
Our architecture targets linear cost growth in sequence length, instead of the quadratic cost of standard transformer attention. That is an architectural claim, and we say plainly below where it stands today.
Competitive positioning
How we compare
| The Brain | Public LLM | Local LLM | RAG | |
|---|---|---|---|---|
| On-premise | Yes | No | Yes | Yes |
| Persistent entity memory | Yes | No | Limited | Limited |
| Long operational histories | Targeted | Expensive | Expensive | Partial |
| Air-gapped capable | Yes | No | Yes | Yes |
| Edge deployment | Yes | No | Limited | Limited |
| Linear cost scaling | In validation* | No | No | Unclear |
*Linear scaling is our core architectural claim. It is being validated on production hardware this quarter.
Beachhead market
Oil & Gas
Picture an operator with 50,000 pieces of equipment. Compressor C-74 gets its own persistent memory: installation history, operating parameters, vibration trends, maintenance events, technician notes.
Instead of asking what an alarm means, the operator can ask why C-74’s vibration profile has changed over six months, and whether that pattern preceded a failure elsewhere in the fleet. The data never leaves their infrastructure.
Honest status
Where we really are
Built and tested
- Production server written in Rust
- Industry-standard interface — existing tools work unmodified
- Deployment and monitoring tooling
In progress · Next 3 months
- Confirm linear scaling on production hardware
- Train the foundation model
- Prove the persistent memory system
We’re being direct: the serving infrastructure is done. The core model claims — linear scaling and persistent memory — are the next three months of work, not finished results.
Business model
Compute vs. intelligence
Customer owns the compute
The customer buys and owns the hardware — roughly $70,000 to $100,000 — giving them full control of their infrastructure and their data.
Rethink owns the intelligence
One-time deployment fee of $25,000 to $50,000, then a recurring platform license starting at $1,500 a month per site, scaling with entities and data volume.
Customer owns the compute. Rethink owns the intelligence. That’s a recurring, high-margin software relationship — not a one-time integration job.
Growth plan
Expansion path
Phase 1
Oil and gas, industrial infrastructure. One beachhead, one paying design partner.
Phase 2
Aviation, transportation, manufacturing. Same entity-memory model, adjacent operational data.
Phase 3
Government and regulated enterprise, once the architecture is proven at scale.
Who we don’t serve
Deliberately narrow. If a workload is mostly free text rather than sequential, entity-tracked data, a general-purpose model is the better tool — and we’d rather say so.
- News and general journalism
- Social and platform content
- E-commerce catalogues
- Scientific literature search
- General business correspondence
- Medical imaging
Investment
The ask
We’re raising $750,000 for 25% of a new company built to hold The Brain: its technology, IP, customers, and revenue going forward.
This raise funds production-hardware validation of the core technical claims and our first paying design partner in oil and gas. That validated customer is the milestone for our next round.
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