About
Built for companies doing real work.
Arctos Field AI exists for founder-led and operator-led companies whose internal systems were built around real deadlines, real customers, and real constraints, not around the AI tools now available.
Greg Berberian
Hard-tech systems experience, applied to AI leverage.
Greg Berberian is a spacecraft mechanical engineer at Umbra, designing deployable reflectors for satellite systems. That work sits where software, suppliers, test plans, documentation, manufacturing constraints, and schedules all collide.
That background shapes the way Arctos Field AI works. The goal is not to add AI for novelty. The goal is to find the places where a company's operating system was never intentionally designed for leverage, then build practical AI/software tools that make the team faster, clearer, and more capable.
- Starts from the operating loop, not the model demo: where decisions, documents, follow-up, approvals, and handoffs actually slow people down.
- Builds with approved company context and human-review gates, so outputs can be trusted before they touch customers.
- Applies hard-tech systems judgment to AI: boundaries, failure modes, verification, and ownership matter as much as prompts.
- Ships bounded proof tracks first, then expands only where the system saves real operator time.
Bias
Useful beats impressive.
The first win is rarely a giant autonomous system. It is usually a sharp internal tool, a better follow-up loop, a source-grounded draft, a decision register, or a private assistant that knows the company well enough to reduce coordination load for the people already carrying the work.
Next
Start with a 30-day proof track.
One overlooked operating loop, one bounded system, one honest continuation decision.