Service

AI that earns its keep in your operations.

We find the workflow where AI actually compounds, build the system that runs it, and hand you the keys with documentation. Production-ready, in your stack, on your infra. Fixed price.

01 / How it works

Three steps. One outcome.

Most “AI consultants” stop at strategy decks. We don’t. We audit the workflow, build the system, and hand you the keys.

Workflow audit

A short, focused review of your operations, data, and tools. We map the workflows where AI compounds — and the dead ends to skip. Output: a written report with ranked plays, effort/impact estimates, and a recommended starting point. No upsell.

Build

We build the system end-to-end. The agent, the integration, the internal tool — production-ready, in your stack, on your infra. Documented, tested, and observable from day one.

Handoff

Code in your repo. Deploys in your accounts. Documentation, training, and the knowledge your team needs to run and extend it. We aim to leave, not to embed.

02 / Engagements

Pick a starting point.

Assessment
$3Kfixed
1–2 weeks

Where AI compounds in your business — and where it doesn’t. Written report, ranked plays, no upsell.

  • Stakeholder + systems audit
  • Ranked list of opportunities
  • Effort/impact estimates
  • 1-hour debrief call
Implementation
Most common
$15K+fixed
3–6 weeks

We build the agent, the automation, or the internal tool end-to-end. Production-ready, documented.

  • Build + deploy in your stack
  • Eval harness for outputs
  • Guardrails + observability
  • Handoff + training
AI partner (retainer)
From $6K/moretainer
Ongoing

We embed with your team. Build, train, evaluate, and ship AI features inside your product or ops.

  • Weekly working sessions
  • Roadmap + measurement
  • Eval + tuning
  • 30-day notice
03 / What that looks like

The shapes AI takes inside a real business.

Example

Manual reconciliation, gone

Two systems that should talk and don’t. We replace the half-day pay-period close, the spreadsheet copy-paste, the Friday-afternoon classification work. Your team gets evenings back.

Example

Operator-facing internal tools

A workflow your ops team owns: queries, drafts, decisions made faster with AI inside the same screen they already use. One-click, not half-day.

Example

AI features in your product

A feature your customers see: drafting, summarization, classification, search. Wired into your existing product with the evals and guardrails to keep it boring once it ships.

04 / Who this is for

Operators with real revenue and too much manual work.

If you run a 10–150 person business, you have data, workflows, and people doing repetitive judgment work — there is leverage hiding in plain sight. We find it and build the system that captures it.

Scenario

The data lives in two systems

A multi-location operator where the same numbers get re-keyed between two systems every week. The handoff is the job — not the work that the job is supposed to produce.

Scenario

Senior people are reading documents

A regulated business — insurance, finance, legal-adjacent — where document review is eating the time of people who could be doing higher-leverage work. The judgment is consistent; the volume is the problem.

Scenario

Intake or routing is a bottleneck

A services business where inbound requests pile up because someone has to read each one and decide where it goes. Response time is the customer experience, and the queue keeps growing.

Scenario

Quarterly reports run on CSVs

An ops team that pulls data from four tools, drops it into a spreadsheet, and produces the same report every quarter. The math is stable; the assembly is manual.

Scenario

You’ve read the pitches and aren’t sure where to start

An owner who’s heard the AI sales decks and isn’t sure which workflow is the right first investment. You want an honest read on where the leverage is, not a vendor demo.

05 / FAQ

Common questions.

We already use ChatGPT — is this different?
Yes. Off-the-shelf chat is a starting line. We build the integrations, automations, and evals that turn AI into actual leverage on the work — inside the tools your team already uses, not in a separate window.
How do you handle data privacy?
Self-hosted or VPC-deployed by default for sensitive data. We use models that don’t train on your inputs and document the boundaries explicitly.
Will my team be able to maintain this?
Yes. Training and documentation are part of the deliverable. The point is leverage you keep, not a black box you depend on us to run.
What if my project goes over scope?
Scope changes are a conversation, not a surprise invoice. We re-quote any change before doing the work. Original scope stays at the original price.
Can you take over a half-built AI project?
Often, yes. We do a short audit first to make sure the codebase is workable. If it isn’t, we’ll tell you straight.
Get in touch

Want an honest read on AI in your business?

A 30-minute call. We’ll tell you what’s real, what’s noise, and where to start.