Choose the problem.
Map the workflow, measure the time it takes today, and agree the outcome worth improving.
A practical route from AI idea to daily use.
Our AI implementation consulting follows four steps. Each one ends with a decision, so you only commit to the next stage when the evidence supports it.
Check the foundations.
Review sample data, system access, dependencies and who approves what.
Test a focused pilot.
Build the smallest useful version and test it against agreed acceptance criteria.
Put it into daily use.
Integrate, document, train the team and agree the support needed afterward.
Before implementationAgree the work
Agree the work
and how it is accepted.
Everything below is written down before development starts, so there are no surprises about scope, cost or what “done” means.
- Outcome
- The task, users and improvement you want to assess
- Scope
- Deliverables, dependencies and exclusions
- Acceptance
- Test cases, review criteria and approval owners
- Delivery
- Milestones, costs and the process for changes
- Operations
- Handover, support coverage and escalation paths
Ways to engage
Match the team
to the work.
AI Opportunity Review
Rank opportunities, assess prerequisites, and scope the first pilot.
Project or embedded team
Commission a scoped build, or add implementation capacity to your consultancy, agency or internal team.
Ongoing support
Agree the review, maintenance and exception-handling workload after deployment.
What you can expect
How we run
an engagement.
One named contact.
A single person owns the engagement and your communication with the team.
Regular check-ins.
Progress, open questions and decisions are reviewed with you on an agreed schedule.
Written decisions.
Scope changes, acceptance and go or stop decisions are recorded, not assumed.
Documented handover.
How the workflow runs, how to change it and who to call is written down before we step back.
Who we work with
Direct clients
and delivery partners.
Small and mid-sized businesses
Owners and operations leads at small and mid-sized US businesses with no in-house AI team.
Consultancies
Firms that advise on AI and need a team to implement and support what they recommend.
Automation agencies
Agencies that need extra capacity for AI workflows, integration or ongoing review.
Data and security
Access agreed
before work starts.
The same rules apply to every engagement, direct or through a partner.
- Confidentiality, permitted access and data handling are agreed in writing before any access is shared
- Work starts on representative samples, not your full data
- Access is limited to the systems the workflow needs, and is removed at handover unless support continues
- Ownership of the workflows, prompts and code we build is agreed in writing before work starts
- Specific compliance requirements, such as SOC 2 or HIPAA, are discussed before any access is shared
Questions
Before
we begin.
Do we need a defined project?
No. The AI Opportunity Review can help clarify the opportunity. If you already have a specification, we can begin with an implementation review.
How are cost and timing agreed?
They depend on scope, systems, dependencies and coverage. The delivery proposal sets out milestones and costs before work begins.
What happens if the pilot does not meet the criteria?
Review the results and agree whether to revise the approach, resolve prerequisites, or stop. Wider deployment follows an explicit acceptance decision.
How is access handled?
Confidentiality, permitted access, data handling and ownership are agreed before information or system access is shared.
Can you work with consultancies and agencies?
Yes. Formals can support a defined engagement or work within an existing delivery team.
Work with FormalsLet’s plan
Let’s plan
the next step.
Discuss the opportunity, the delivery requirements, or support for an existing system.
Book an AI Opportunity Review