AI Automation Consulting
A short diagnostic session, then a build process you stay in control of: automation that is safe to run, easy to watch, and asks for your yes before anything risky.
Most AI pilots never reach production. Research from RAND has found that more than 80 percent stall out before they deliver a return, often because the work was automated before it was understood. AI Automation Consulting starts with a Clarity Sprint: one focused session that maps the manual loops, decisions, handoffs, and approval points in your operation, and produces a prioritized view of where automation pays off the most. When a build follows, it runs through Governed AI Automation Builds: a seven-phase method, Research to Spec, Scope, Execute, Verify, Release, Operate, Improve, with a named checkpoint where a person signs off at every phase. A knowledge base is built alongside the automation so the system has the context it needs, and every phase carries a checkpoint you can see and approve. The result is automation that moves fast inside boundaries you set, and stays visible the whole time it runs.
How it works
- Research to Spec
Gather evidence and define the outcome, scope, and non-goals before any build starts. Gate: the written plan is approved before scoping begins.
- Scope
Break the plan into small, clearly bounded tasks, each with the files it can touch and the limits it runs under set in advance. Gate: tasks are sized and spending caps are set.
- Execute
Work is handed out and tracked, with cost and which AI is doing what kept in view. Gate: low-risk steps run on their own, everything else waits for your review.
- Verify
Every task carries a test, a review, and proof before it counts as finished. Gate: no proof, not done.
- Release
Changes move through a reviewed path before they reach your live system. Gate: a code review and a recorded change log.
- Operate
Health checks and dashboards watch the system once it is live. Gate: a clear ranking of how serious an issue is, and a path to escalate anything that needs a person.
- Improve
Lessons from each cycle are captured into your knowledge base and a running list of things to tidy up later. Gate: a review of what was learned and how the system is maturing.
Who this is for
- founders
- operators
- businesses
Frequently asked questions
Why do most AI automation pilots fail to reach production?
Research from RAND has found that more than 80 percent of AI pilots stall before they reach production, usually because the work was automated before anyone mapped how it actually worked. The Clarity Sprint exists to answer that question first: what the workflow really involves, where the risk sits, and where automation pays off, before any build begins.
What stays under human approval once the automation is running?
Anything with legal, financial, reputational, or relationship risk. That includes payments, refunds, pricing, contract terms, sensitive data, external publishing, destructive or irreversible changes, and anything the system itself is unsure about. Those approval gates are set once, by you, and the system runs fast inside them.
What do I get from a Clarity Sprint before committing to a build?
A clear map of the work, decisions, handoffs, and bottlenecks that currently run on manual effort, a prioritized view of where automation pays off the most, and the inputs needed to scope a build if you decide to move forward.
Consulting and engineering delivery service only. Nothing on this site constitutes legal, tax, or financial advice.
Ready to get started?
Book a session to scope the engagement.