Audit. Plan. Build. Deploy. Then keep improving.

Most failed AI projects fail in the same place: someone started building before anyone agreed what success looked like. Our process is designed so that never happens — every stage ends with a deliverable in your hands and a decision that's yours to make.

Start at stage one — it's free

01Week 1 · Free

Audit & Discovery

We start by watching, not proposing. A structured working session with the people who do the work, a walk through your actual systems, and a short questionnaire covering volumes, costs and pain points.

The output is a ranked register: every process we think is automatable, scored on effort versus payback. Some of them we'll tell you not to bother with. That honesty is the point — it's how you know the recommendations you do get are real.

Deliverables

Current-state process maps
Ranked automation opportunity register
Volume, cost and error-rate baseline
Estimated ROI and payback per opportunity
Recommended starting point

02Week 2

Planning & Solution Design

We take the top-ranked opportunity and design it properly before writing code. Which model and why. Which platform. Which systems it touches and what happens when one of them is down. Where a human must stay in the loop, and what threshold triggers that.

You get a fixed-scope statement of work with a fixed price. No hourly meter, no scope creep conversations three weeks in.

Deliverables

Technical architecture and data flow diagram
Security, privacy and compliance plan
Human-in-the-loop and fallback design
Success metrics agreed up front
Fixed-scope SOW with timeline and price

03Weeks 3–6

Development & Build

Two-week sprints with working software at the end of each. You get staging access from day one and a weekly demo — you'll never be surprised by what shows up at the end.

Reliability work happens alongside features, not after them: evaluation suites that measure accuracy against real cases, structured logging, retry logic, cost ceilings, and graceful degradation when an upstream service fails.

Deliverables

Working system in staging, every sprint
Evaluation suite with accuracy benchmarks
Automated tests and CI/CD pipeline
Source code in your repository from day one
Weekly demo and written progress note

04Week 7

Deployment & Enablement

We never flip a switch and walk away. Rollout runs in phases: shadow mode where the system processes real work but a human still decides, then partial volume, then full — with a defined rollback at every stage.

Meanwhile your team gets trained. Runbook, monitoring dashboard, override controls, escalation paths. The goal is that you could operate this without us.

Deliverables

Phased production rollout with rollback plan
Monitoring dashboards and alerting
Operational runbook and documentation
Live team training sessions
30 days of hypercare support

05Ongoing

Optimisation & Scale

The first automation is the hardest. Once we know your systems, your data and your team, each subsequent one gets faster and cheaper to build. Most clients go from one workflow to a portfolio within a year.

We monitor accuracy and cost, tune prompts and thresholds against real production data, migrate to better models as they ship, and keep a live roadmap of what's worth doing next.

Deliverables

Monthly performance and savings report
Accuracy tuning against production data
Model and cost optimisation
Rolling roadmap of next opportunities
Defined support SLA

Non-negotiables

Five rules we don't break

Learned the expensive way, mostly by watching other people's projects fail.

Measure before you build

If we can't state the current cost of a process in hours or dollars, we can't prove we improved it. Baseline first, always.

Ship narrow, then widen

One process, done to production quality, beats five half-built pilots. Momentum comes from something that actually works.

Design for the failure case

What happens when the API is down, the model is wrong, or the input is nonsense? Answered before launch, not after an incident.

Keep a human at the edge

Confidence thresholds and review queues aren't a lack of ambition — they're what makes automation trustworthy enough to expand.

No lock-in, ever

Your code, your cloud, your keys, your documentation. If you fire us tomorrow, everything keeps running.

Say no to bad ideas

We turn down work where the numbers don't justify it. A failed automation costs you more than the one you didn't build.

Your side

What we need from you

Less than you'd think — but the things we do need are non-optional. Projects stall when access takes six weeks or nobody can make a decision.

One decision-maker
Someone empowered to approve scope without a committee. Two hours a week is enough.
Access to the people doing the work
A few hours during discovery. They know the process the documentation forgot.
System access, arranged early
Read-only to start. IT approval is the single most common cause of delay, so we raise it in week one.
Real examples, not sanitised ones
The messy edge cases are what determine whether a system survives contact with reality.

Stage one is free

Begin with the audit

You'll get a written opportunity register with estimated savings — yours to keep, with no obligation to continue.

Book your free automation audit See what we build