Advice that stays for the build.
The hard part of AI strategy is deciding which bets are worth making, lining up the data, security and legal answers, and seeing the first ones through. Our consultants are engineers, and they work inside your teams until the decisions turn into running systems.
Transform
What we deliver
AI readiness assessment
Your data, systems, skills and policies reviewed against the use cases you care about, with the gaps sized.
Use-case portfolio
Opportunities scored by value, feasibility and risk, so you fund the few that matter.
Architecture and build-versus-buy
Reference architectures and vendor evaluations based on your constraints rather than a partner list.
AI governance and policy
Usage policies, model risk controls and review processes aligned with the EU AI Act, GDPR and India's DPDP Act.
Engineering practice uplift
AI coding tools, evals and agent workflows brought into your own engineering teams, with measurement.
Fractional technical leadership
Experienced engineering leaders, part-time, to steer AI and platform decisions.
How it runs
From first week to handover.
Durations are typical. We agree the actual plan with you during scoping.
Listen
Week 1Interviews with leadership, operators and engineers, plus a review of systems and data.
Assess
Weeks 2 to 3Readiness findings and a scored use-case portfolio, presented as decisions to make.
Plan
Week 4A 90-day roadmap with owners, budgets, governance steps and the first builds specified.
Deploy
OngoingConsultants stay embedded to run the first builds with your teams or ours, and adjust the plan as results come in.
AI in the loop
How we keep it practical
Evidence over opinion
Short technical spikes on your own data test whether a use case works before it goes on the roadmap.
Your engineering, measured
We baseline delivery metrics before introducing AI tooling, so you can see what changed.
Governance that ships
Policies come with the checks that enforce them: approved models, logging and review gates.
Practitioners, not presenters
Every consultant can build what they recommend, which keeps recommendations realistic.
What you own at the end
- A scored AI use-case portfolio
- A 90-day roadmap with owners and budgets
- An AI usage policy and governance process
- Reference architecture and vendor recommendations
- Baseline delivery metrics for your engineering teams
Ways to engage
Readiness sprint
A defined question answered: an assessment, an architecture review or a scored use-case portfolio.
Embedded advisory
A consultant or fractional engineering leader inside your organization a set number of days each month.
FAQ
Questions we hear.
Is this a one-off assessment?
It can be. Many clients keep a consultant embedded part-time after the assessment to steer delivery and adjust the plan.
Do you resell AI platforms?
No. We have no reseller arrangements, so recommendations follow your requirements.
Who will we work with?
Senior engineers and architects with delivery experience, supported by specialists in data, security and compliance as needed.
Can you help with regulation such as the EU AI Act?
We help you classify use cases, design the technical controls and document them. Legal sign-off stays with your counsel.
Related
Often paired with.
Build
AI-First Product Engineering
Products designed around models from the first sprint: agents, copilots, retrieval and automated workflows, built with evals, guardrails and cost controls.
Extend
Forward-Deployed Engineering
Senior engineers embedded in your business who own a problem end to end, from the first conversation with users to the system running in production.
What are we building?
Tell us about the problem. An engineer, not a sales team, will reply.