Recorded client call
“I find him very nice to work with and he actually delivers a very good quality. So I am really happy with him.”
Noa van der Veen · Strategy and operations, CheckyPro
Engineering enablement
AI-Enabled Teams
We build with your engineers, integrate AI into the way they already ship, and leave behind tooling and practices they can operate without us.
Partnerships and reviews
Certified partnerships
Rated by clients and team
- Clutch
What you get
Capability that stays with your team
Delivery and enablement run together. We use real product work to find what helps, then turn it into repeatable tooling and practice.
Paired delivery
Our senior engineers work alongside yours on live product work. Your team learns AI-assisted delivery by doing it, not watching a workshop.
AI-assisted engineering workflows
Code-generation, review, test-writing, debugging, and documentation workflows fitted to your codebase, standards, and release process.
Internal agents + tooling
Repository-aware agents, support copilots, and operational automations that live in your stack and remain yours after the engagement.
Evaluation playbooks
Repeatable methods for assessing prompts, models, and agent outputs: including where human review is mandatory.
Hands-on team training
Working sessions built around your code and delivery bottlenecks. No generic prompt decks and no training theatre.
Adoption measurement
Baseline and follow-up measures for cycle time, review load, defects, and AI-tool adoption so you can see what actually changed.
We build with your engineers: not in a separate repo.
Delivery
How the engagement runs
- Phase 1
Workflow audit
We map how work currently moves from ticket to production, where engineers lose time, and which AI interventions are worth testing.
- Phase 2
Pilot on real work
A small group pairs with us on a live delivery stream. We test tooling and guardrails against your codebase, not a sandbox repository.
- Phase 3
Tooling + playbooks
We productionise the workflows that worked, build internal integrations, and document the decisions your wider team needs to repeat them.
- Phase 4
Rollout + handoff
Hands-on sessions, office hours, adoption tracking, and an explicit handoff. The goal is for your team to keep improving without us.
Capability transfer
The tooling stays. The capability stays. We optimise for leaving.
We pair with your engineers on production work, build tooling into your repository, and hand over playbooks your team has already used. The goal is not to be needed indefinitely: it is for your team to keep improving after we leave.
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Fit
Who this is for
Best for
- Engineering teams already experimenting with AI but lacking a safe, repeatable workflow
- Leaders who want measurable delivery gains rather than a company-wide prompt workshop
- Teams building AI features that need stronger evaluation habits
- Organisations that want capability transfer, not permanent dependency
Not for
- A request for engineers with no enablement or knowledge-transfer goal: see Staff Augmentation
- A one-off AI feature you want us to own end to end: see AI Development
- A leadership-only seminar with no access to real engineering work
Related services
Different ownership model? Start here.
Testimonials
What founders say after the build
Verbatim quotes from teams we shipped to production. We publish testimonials with written sign-off on file.
4.6/5across 58 verified client reviews.Read them all at source
Questions engineering leaders ask
The goal is operational capability, not an impressive workshop. Here is how we keep the engagement grounded.
No. Training without real delivery rarely changes how a team works. We pair with your engineers on production work, build tooling into your repository and delivery stack, then use focused sessions to reinforce the practices they have already applied.
Want your team to ship better with AI?
Bring us one real delivery bottleneck. We will show you where AI can help, where it cannot, and how to transfer the capability without creating a permanent dependency.