AI that holds up in daily use.

Custom AI built inside your operation: automation, decision support, and smarter processes, with checks and human accountability designed in from the start.

What we deliver

Custom AI & intelligent automation, in full.

Our flagship practice: AI systems built for operations where a wrong answer has a real cost.

  • Custom AI systemsDecision support and process automation built for your operation. Works with any major AI provider: Amazon Bedrock, Azure OpenAI, Google Vertex, and Anthropic.
  • Automated processingHigh-volume work handled from start to finish, with exceptions routed to named reviewers along with the evidence they need.
  • Human review built inEvery answer cites its source, carries a confidence score, and goes to a named person before it takes effect.
  • Connected to your systemsLinked to the platforms you already run, under your sign-in system and security policies. See our integration practice.
  • Testing & monitoringAccuracy measured on your real data before go-live, and monitored after, so drift shows up on a dashboard rather than in complaints.
How it runs

Scoped. Built. Handed over.

Every engagement runs under a master agreement with a scoped statement of work for each phase, and ends with documentation and training your team owns.

01 · Prove

Test on your data

The candidate process tested on realistic data against clear accuracy thresholds before the build is scoped.

02 · Deliver

Put the first version in use

A first working version in daily use within 30 days, connected, checked, and measured.

03 · Expand

Grow one process at a time

Coverage extended in phases, each with its own success criteria and a documented handover.

Hands-on leadership Statement of work per phase NDA, BAA, DPA as required Documented handover
03 The standard

AI counts when it runs in your daily operations.

The distance between a demonstration and a dependable system is connection, checking, and governance. That distance is exactly what we build.

Start here

Put AI to work where it holds up.

Bring the process that costs your team the most. We'll describe what a dependable system looks like and prove it on your data first.