Opportunity mapping
Interviews across the business to find decisions and workflows where AI saves time, money or risk.
AI Strategy & Roadmaps
An AI strategy your board and your engineers both believe in.
We find where AI actually moves your numbers, size the value, check whether your data can support it and sequence a roadmap that starts with the use cases most likely to pay off. Then we can build it with you, so the plan does not end as a slide deck.
The problem
Why this work usually stalls.
01
Too many ideas, no priorities
Every team has an AI wish list. Without a way to compare value, feasibility and risk, the loudest idea wins.
02
Pilots with no business owner
Projects start because the technology is exciting, not because someone owns a metric that will move.
03
Data that is not ready
Most roadmaps assume clean, connected data. Most companies find out it is neither halfway through the first project.
04
Strategy that stops at the deck
Advisory work that is never built leaves leadership with a plan and no working system.
What we deliver
AI Strategy & Roadmaps, built for production.
Pick one piece or the whole programme. Each is scoped to a business metric and shipped, not left as a proof of concept.
Use case prioritisation
A ranked backlog scored on value, feasibility and risk, so you know what to do first and what to leave alone.
Business cases
Clear, caveated estimates of benefit and cost for the top use cases, in terms your finance team will accept.
AI and data readiness assessment
An honest look at your data, platforms, skills and governance, with the gaps that matter for your roadmap.
Operating model
Who owns AI, how projects are approved and measured, and which skills to build in house versus buy.
Roadmap and first build
A sequenced plan for the next 12 to 18 months, and the first pilot scoped so it can start straight away.
How we deliver
From first call to production.
Every phase ends with something you can use, not just something you can read.
Always included
- A senior squad of two to four people, led by an engineer from companies like Amazon, Google or Microsoft
- Weekly demos and one business metric agreed upfront
- Founder review every week and sign-off before production
- All code, models and documentation owned by you
Typical tools
01
Weeks 1 to 2
Listen and map
We talk to the people who run the business and the people who run the systems.
- Stakeholder interviews across functions
- Map key decisions, workflows and pain points
- Review existing data, platforms and past AI attempts
02
Weeks 2 to 3
Score and size
Every idea is scored the same way, so priorities are clear and defensible.
- Value, feasibility and risk for each use case
- Data readiness check for the top candidates
- Caveated business cases for the shortlist
03
Week 3 to 4
Roadmap and operating model
A plan leadership can approve and engineers can execute.
- Sequenced 12 to 18 month roadmap
- Ownership, governance and success metrics
- Build, buy or partner recommendations
04
Weeks 4 onward
First pilot
We help you start, so the strategy turns into a working system.
- Pilot scoped against one agreed metric
- Senior squad ready to build
- Progress reviewed with leadership
Where we apply it
Industries we know well.
Further reading
From the blog.
AI Readiness Assessment: A Practical Checklist for Leaders
A scored AI readiness assessment checklist covering strategy, data, technology, people and governance, with a simple rubric and guidance on what to fix first.
AI Implementation Cost in India: Drivers, Ranges and Budgeting
A practical guide to AI implementation cost: the real cost drivers, indicative ranges by project type, the running costs people forget and how to budget sensibly.
AI Consulting Services in India: How to Choose the Right Partner
What AI consulting services in India should actually deliver, how to evaluate firms, the questions to ask and the red flags to watch for before you sign.
FAQ
Questions we hear a lot.
How long does an AI strategy engagement take?
Usually three to four weeks for a focused discovery and roadmap. Larger organisations with many business units may take longer. We keep it short on purpose, so you can move to building quickly.
What do we get at the end?
A ranked backlog of use cases with value, feasibility and risk, business cases for the top ones, a data readiness view, an operating model and a sequenced roadmap. We also scope the first pilot so it can start right away.
Do you only advise, or do you also build?
We build. The same senior team that writes the roadmap can deliver the first pilot, which keeps the strategy honest about what is actually possible.
How much does an AI strategy engagement cost?
We work on fixed-fee sprints, so you know the price before work starts. The fee depends on how many business units and systems are in scope. Our article on AI implementation cost explains the main cost drivers.
Other services
Everything between ambition and production.
GenAI & AI Agents
Copilots, retrieval systems and agents wired into your real tools and data.
Data Platforms & Engineering
Lakehouses, clean pipelines and governed metrics that every model depends on.
Analytics & Decision Intelligence
Forecasting, pricing, churn and demand models, plus dashboards people open.
MLOps & AI Engineering
CI/CD for models, observability and cost controls that keep AI reliable.
Digital Transformation & AI Governance
Process redesign, change and responsible AI aligned with the DPDP Act and EU AI Act.
Managed Services
Cloud, DevOps, QA and release management, run 24x7 against clear SLAs.
Talk to a founder about AI Strategy.
Tell us where you are. We will come back within one business day with a point of view, not a sales deck.