Agentic
transformation that
outlasts the pilots.
Stand up an AI-native delivery organization: operating model, shared platform and the governance to scale it safely.
Trusted on systems that cannot fail
When pilots stop being enough.
Pilots are easy to run and hard to scale. Making AI-native delivery the default requires an operating model, not a tool rollout.
- 01
Nothing composes across teams
Each team found its own tools, prompts and habits. None of it carries over to the next team.
- 02
Risk and legal have stopped the rollout
Without governance, scale is a liability question rather than a technology one.
- 03
The board asked for numbers
Adoption is not a metric. Throughput, rework and escape rate are.
AI delivery transformation, from assessment to rollout.
One team, accountable for the whole lifecycle, not a slice of it.
Transformation roadmap
A sequenced plan from pilot to org-wide AI-native delivery.
Operating model design
Roles, teams and workflows redesigned around agentic delivery.
Governance and guardrails
Policies, gates and audit trails that make AI use safe at scale.
Platform and tooling
The shared harness and platform every team builds on.
Rollout and change management
Adoption handled as change, not just tooling, so it sticks.
Metrics and improvement
The metrics and feedback loops that keep throughput and quality climbing.
The operating model, written down.
Governance, platform and rollout artifacts your organization keeps running after we leave.
Strategy
- Roadmap from pilot to org-wide
- Operating model and role design
- Governance and risk framework
- Business case with target metrics
Platform
- Shared harness and internal platform
- Standard spec and test templates
- Policy, audit trail and access controls
- Reference implementations per stack
Rollout
- Wave plan by team and product
- Enablement and champion programme
- Metrics dashboard and review cadence
- Continuous improvement loop
- Pilots become one repeatable delivery model instead of isolated experiments.
- One platform and one governance model across teams, not tooling per team.
- AI-assisted delivery carries the same audit trail as the rest of your engineering.
Spec-driven, AI-assisted
delivery, governed end to end.
AI agents build. Senior engineers hold the gates. The framework that turns AI speed into governed, predictable delivery, from the first call through to support after launch, in five phases you can point at.
- 01
Assess
We map the system, risks and constraints. Honest, fast, no obligation.
- 02
Spec
Requirements become behavior-first specifications before any code.
- 03
Build
AI agents build from the specs; senior engineers hold every gate.
- 04
Govern
Tests, hooks and reviews enforce the standard continuously in CI.
- 05
Ship & scale
Release, observe and harden. Throughput grows as the harness learns.
- Faster time to market
- 30-50%
- Less rework and rip-out
- 40-60%
- Delivery throughput per engineer
- 2-3x
- Requirements covered by tests
- 90%+
What we build it with.
Chosen for what your team can operate and hire for, not for what is new.
Platform
Governance
Delivery at scale
Measurement
Five levels. Most organizations we assess sit at one.
The assessment places you honestly, then the roadmap moves you one level at a time. Nobody goes from ad hoc to scale in a quarter.
-
Level 0
Ad hoc
AI use is individual and invisible. No policy, no measurement.
-
Level 1
Sanctioned
Approved tools and a usage policy. Results still depend on who uses them.
-
Level 2
Governed
Shared harness, specs and review gates on one team, with a measured baseline.
-
Level 3
Platform
One platform and one governance model across teams, reviewed on a cadence.
-
Level 4
Scaled
AI-native delivery is the default, and the metrics improve release over release.
How the rollout runs
In waves, each one measured before the next begins.
-
One team, one real deliverable
Baseline measured before and after. If the numbers do not move, the roadmap changes.
-
Shared platform, more teams
What worked in wave 1 becomes the shared harness and governance the next teams build on.
-
Org-wide default
Remaining teams join by plan, with champions from earlier waves leading enablement.
Adoption happens with your
engineers, not around them.
The operating model only holds if the people using it believe in it. Our engineers pair with your teams, run the reviews with them and hand the practice over once it runs without us.
How we work together
Three shapes. After the assessment we tell you which one fits, including when the answer is none of them.
Readiness assessment
Understand what scale would require.
- Commercials
- Fixed price, roadmap and costed options
- Typical duration
- 3-4 weeks
Pilot to platform
One wave, then the shared platform.
- Commercials
- Phased, gated by wave
- Typical duration
- 4-6 months
Transformation partnership
Org-wide rollout with us alongside.
- Commercials
- Named team, quarterly planning
- Typical duration
- 12+ months
Every engagement starts with an assessment. It is fixed price, it ends in a written plan, and the plan is yours whether or not you continue with us.
Certified, accredited and independently reviewed
- Built to SOC 2 Type II criteria
- GDPR-compliant processing, DPA available
- NDA and IP assignment as standard
Explore other services
All servicesFrequently asked questions.
Something not covered here? Ask an engineer directly, no SDRs, no funnel.
How is this different from engineering uplift?
Engineering uplift brings one team onto the Agentic SDLC. Agentic transformation makes it the default across the organization: operating model, shared platform, governance and a rollout plan by wave.
Do we have to stop our current AI pilots?
No. The assessment starts from what your pilots already do, keeps what works and turns it into the first wave rather than starting over.
How do you satisfy risk and legal?
Governance comes before scale: usage policy, access controls, review gates and an audit trail for AI-assisted work, so it is held to the same standard as the rest of your engineering.
How do we report progress to the board?
With throughput, rework and escape rate measured against the baseline from the assessment, wave by wave. Adoption numbers alone are not reported as success.
What happens when the partnership ends?
The platform, the governance framework, the playbooks and trained internal champions stay with you. Every wave hands over to your teams before the next one starts.
Let's Work Together
German engineering discipline meets agentic delivery. Send a short note and we'll reply within one business day, straight to an engineer, no SDRs, no funnel.
- Email[email protected]
- Phone(+84) 246.276.3566
- Response TimeWithin 1 business day