Services

Services

AI implementation services, custom AI solutions, and AI automation — from strategy to production. Practical AI delivery for enterprise teams.

What we do

A focused menu, priced to outcomes.

Pick a single service or let us scope the combination. Every engagement starts with a written brief and a fixed budget.

Deep dive

AI Implementation Services

We design, deploy and hand over secure-by-default cloud-AI environments on Azure, AWS or GCP — identity, networking, private endpoints, RAG ingestion and observability, in 16 ordered steps.

Process-first design
Enterprise security by default
Continuous iteration

— Regular dev team vs AI-augmented team

Metric
Regular
SMH AI
Delivery velocity
2.8×faster
Time to production
30 wk
12 wk
Engineering cost
$$$$
$$lower
Test & eval coverage
35%
80%
SMH Benchmarks · 2024–2026Cloud-AI · RAG

40+

AI systems shipped

12 wk

Median time to prod

94%

Pilots reaching v1

2019

Building agents since

How we work

Four stages, one team, zero handoffs.

The same senior engineers who scope your project are the ones who build it. No account manager theater.

01

Discovery

Two weeks of interviews, workflow mapping and a written brief. You get a scoped plan and a fixed bid before anything else.

02

Prototype

A working, evaluable prototype against your data — not slides. We measure it, then decide together whether and how to scale.

03

Production

Harden, integrate, secure and deploy. Eval harness, observability and rollback are part of the deliverable, not an afterthought.

04

Adoption

Enablement, playbooks and quarterly reviews. We stay on as much or as little as you need once the system is live.

FAQ

Answers to the questions we get most.

Something missing? Ask us directly — a real engineer will reply.

Most projects start with a fixed-fee discovery (2–3 weeks), followed by sprint-based delivery. We scope to outcomes rather than hours, and share a transparent budget before any code is written.

Yes. We integrate with your cloud, databases, identity and tooling — including private or on-prem deployments. We bring patterns, not opinions, about where code should run.

We are model-agnostic. We regularly ship systems on Anthropic, OpenAI, Google and open-weights stacks, and choose per task based on our benchmarking work.

Every engagement starts with a threat model and data-handling review. We support SOC 2, GDPR and industry-specific regimes, and keep sensitive data inside your perimeter by default.

You get full ownership of the code and a monitored runbook. We offer optional retainers for evaluation, tuning, and new features as your usage grows.

Next step

Tell us the workflow.
We'll tell you if AI fits.

30-minute call with a senior engineer. Bring one problem and the context around it — you leave with a candid read and a next step.

What you get

Candid fit assessment
Rough scope & budget
Sample eval plan
No sales pitch