Forward-deployed AI services

Delivered AI for the mid-market. Not decks. Not tools.

We embed inside your operation, ship the working thing, and stay accountable for the outcome. Built for operators the labs and the Palantir tier will not take.

Schedule a discovery call

How the work runs

Three steps. One operator-grade outcome.

Embed

Two weeks inside the operation

An operator-led team moves into your business and works alongside the people doing the work. The team maps what already works, names what does not, and surfaces which vendors are selling something that will never ship. Output is a decision, not a deck.

Ship

Build the working thing

From the decision, the team scopes a named outcome with a date attached and starts shipping. Platform infrastructure is already proven in production. The work product is the system running in your operation, not a prototype handed back with a roadmap.

Measure

Numbers on the wall, then handoff

Before-and-after numbers ride on every engagement: cycle time, dollars saved, throughput, error rate. When the named outcome lands, the team trains your operators, hands the system over, and steps back. No retainer, no open-ended advisory.

Engagement model

Named

outcomes with dates and numbers attached

Scope

Fixed

no retainer, no scope creep

Handoff

Clean

your operators own the system when work closes

Why this gap exists

The labs are too far up. The consultants are too far out.

The AI labs sell models to companies that already have AI teams. The big consultancies hand a deck to a partner and bill against discovery. Generic AI consultants know the cloud console and not the operation. Mid-market operators sit in the gap — paying real money to vendors who do not ship, or watching incumbents win because the incumbent finally figured out where the actual constraint sat. BREW212 closes that gap by deploying proven services backed by platform infrastructure that has already shipped real outcomes in production. The team operates the way a serious operator runs a P&L: scoped, dated, accountable.

Active engagements with private clients are in flight. Named-outcome case studies publish here as engagements complete and clients clear the writeup. In the meantime, the team is happy to walk a qualified operator through specifics on a discovery call.

How an engagement runs

Four phases. One named outcome.

Evaluation

Two-week operator evaluation

The team walks the operation, talks to the people doing the work, and maps the actual workflow. At the end, you get a written read: where AI services move the number, where they do not, what the named outcome should be, and what it will cost to ship.

Build

Scoped build against the outcome

Engagement contracts on a single outcome with a date and a number attached. The team builds against that contract — no retainer, no scope creep, no quarterly reviews of work that should already be running.

Measure

Operate, instrument, prove

The system runs in production against the agreed metric. Telemetry shows the before-and-after. If the number does not move, the team owns that publicly to you — and the team works the next iteration until it does.

Handoff

Trained operators, clean exit

When the outcome lands, your operators run the system. Documentation is operator-grade — written for the people who will own it. Support continues on a fixed window; advisory does not extend by default. Clean handoff, no permanent dependency.

Phase 1

2wk

Phase 2

Build

Phase 3

Operate

Phase 4

Handoff

If a named outcome is what you need, the discovery call is the next step.

Schedule a discovery call