Controls agreed before access
BS7858 screening before access; client-approved tools and infrastructure.
Read the security commitmentsForward-deployed AI engineers
Forward-deployed AI engineers, embedded in your team
Tenhaw’s AI engineers pair with your team in your repositories, under your controls. Start with a £20,000–£55,000 fixed proof of concept.
Controls agreed before access. BS7858 screening before access; client-approved tools and infrastructure. Read the security commitments.
Book a 30-minute call
See the evidence and approach30 minutes with James Rooney to discuss your team, workflow and first scope.
The job to be done
What we can help you deliver
For engineering and technology leaders who need experienced builders alongside their people, with the code, decisions and operating knowledge held in their own organisation.
Build in the repositories your team owns
Your branch protection, review rules and access controls apply. Agree who reviews and approves changes while your engineers pair on the build.
Develop the ability to run what is built
Pair on the real workflow throughout the engagement. Your engineers learn the requirements, checks and operating method as they help build it.
Choose the next investment with evidence
Use a two-to-four-week proof of concept to test one workflow. Decide whether the production scope merits a 90-day programme before committing to it.
Use a 30-minute call to discuss the outcome your team needs.
Book a 30-minute callWorking together
Build the capability around real work
- 01
Agree the workflow and the controls
Choose one workflow, its acceptance examples, data access and the people available to pair. Set the scope and fee before work starts.
- 02
Pair through requirements and implementation
Turn the requirements into a shared record, resolve gaps with subject-matter experts and build against the agreed examples in your environment.
- 03
Plan for your engineers to take over
Keep code and documentation in your repositories and agree the handover. After the 90-day programme, continuation is a separate monthly decision.
Ask how this approach would fit your data, systems and team on a 30-minute call.
Book a 30-minute callEvidence and approach
Read the evidence behind the approach
Paired engineering at PPL
At PPL, a six-month Embedded Agentic Lead engagement included a two-week greenfield working proof of concept, paired with a client engineer. It did not enter production.
Read the PPL proof of conceptBook 30 minutes to ask James about the work and how it relates to your situation.
Book a 30-minute callScope and price
Choose a starting engagement
Agree the workflow, deliverables and team before work starts. These are the existing engagements this use case can sit within; prices exclude VAT.
Agentic Proof of Concept
Fixed price · £20k–£55k
2–4 weeks
Build and test one AI workflow in your own tenancy.
See scope, team and terms90-day outcome programme
Fixed price · £120k or £180k
90 days
One workflow in production and in use in 90 days.
See scope, team and termsContinue after 90 days
£70k–£85k / month
Month to month after day 90
Keep the team only while the next outcome needs it.
See scope, team and termsUse a 30-minute call to decide which scope is a sensible starting point.
Book a 30-minute callRead further
Explore the method and related use cases
- Tenhaw, London AI consultancy
- Compare the published engagements
- What a forward-deployed engineer does
- Compare an engagement with hiring contractors
- Use the published delivery method
- AI agents and workflow automation
- Enterprise AI assistants
- AI product development
- AI training and adoption
- AI governance, risk and controls
- AI transformation programme
- AI-native delivery
- Insurance document processing with AI
book a call
Talk through the work you want to change.
A 30-minute discovery call with James Rooney. Bring a workflow, product or team challenge and we will discuss a sensible first scope.
most start with a fixed-price AI Readiness Audit · £44,000 · 4 weeks · working prototypes
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Describe the work
Describe the work in a paragraph. James replies with a rough scope and budget range within two working days.
Frequently asked questions
What does a forward-deployed AI engineer do?
They build inside your repositories and infrastructure alongside your engineers, under your policies and access controls. The work includes requirements, implementation, testing and the operating knowledge your team needs to extend the system.
How is that different from a contractor?
A contractor usually fills capacity in a plan you manage. Tenhaw supplies an agreed engagement with partner oversight, pairing, deliverables and a handover. There is no introduction fee or permanent-placement conversion clause.
Do our engineers review and merge their code?
Yes, where that is how your repositories work. Your branch protection, review rules and merge gates apply. Agree the approver role before work starts so the person building a change is not also its only check.
How much of our engineers' time does pairing take?
The engineers you nominate need to be freed up for delivery work throughout the build. Pairing happens on the real system, rather than as training added afterwards. The allocation depends on the scope and how widely you want the capability held at handover.
What do forward-deployed AI engineers cost?
The published senior practitioner rate is £1,250 a day, excluding VAT. They are supplied through engagements: a £20,000–£55,000 fixed proof of concept, a £120,000 or £180,000 90-day programme, or a separately agreed £70,000–£85,000 monthly continuation team.
Are they screened?
Every person is screened to BS7858 standard before client access and works under written confidentiality and data-handling terms. Client-approved tools and your own access controls apply.
What happens when the engagement ends?
Your team keeps the requirements, code and documentation; ownership of client-specific deliverables transfers on payment. The 90-day programme includes handover. Optional continuation is agreed separately, with 30 days’ written notice either way.
Do our engineers need AI experience?
No. They learn the working method while pairing on the real system. Knowledge of your systems and time to take part matter more than prior AI experience; the delivery method is published free so they can read it before the engagement.