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AI Strategy & Advisory

Find the AI opportunities worth funding, prove them on your own data and leave with a roadmap your board and your teams can both believe in.

Overview

AI strategy that ends in shipped software.

Most organisations do not lack AI ideas. They lack a way to tell which ideas will pay back, which ones their data can actually support, and what it will take to run them safely once the pilot is over.

Our advisory work answers those questions with evidence. We map how work really flows through your business, score each candidate use case on value, feasibility and risk, and test the strongest ones with working prototypes on your own data before anyone commits a large budget.

Because the same team goes on to build what we recommend, our roadmaps are written in engineering terms: the systems to connect, the data to fix, the controls to put in place and the outcome each phase must deliver.

When it fits

Signs you need a strategy, not another pilot.

  • Pilots stall after the demo

    Proofs of concept impress in a meeting but never reach the people who do the work.

  • Every team bought its own AI tool

    Spending is spread across overlapping subscriptions with no shared data, security model or measurement.

  • The board wants a plan, not hype

    Leadership is asking what AI will return, when, and at what risk.

  • Nobody owns AI risk

    There is no rule on which data may go into which model, or who signs off automated decisions.

What ships

What the engagement delivers.

  • Opportunity map

    Every candidate use case across your functions, sized by value, effort and risk on one page.

  • Readiness assessment

    An honest view of the data, integrations, skills and access each use case depends on.

  • Business cases

    Baselines, target metrics and cost models, including model usage and running costs.

  • Working prototypes

    Data-backed prototypes of the top use cases, tested with the people who will use them.

  • AI policy and governance

    Acceptable-use rules, data classification for AI, approval paths and risk ownership.

  • Phased roadmap

    A sequenced plan from first workflow to scaled programme, with build estimates and team design.

Use cases

Where strategy work usually starts.

Opportunity discovery

We interview the people who run the work and map the steps, hand-offs and systems involved, looking for repetitive judgement, slow approvals and knowledge that is hard to find. Each opportunity is written up with its trigger, inputs, decision and outcome.

  • Function-by-function process mapping
  • Value, feasibility and risk scoring
  • Quick wins separated from strategic bets

Process

How the engagement runs.

  1. 01

    Frame

    Agree business goals, constraints and the functions in scope.

  2. 02

    Discover

    Interviews, process mapping and a review of your data and systems.

  3. 03

    Prioritise

    Score opportunities and pick a first workflow with a clear baseline.

  4. 04

    Prototype

    Build a working prototype on real data and test it with users.

  5. 05

    Plan

    Hand over the roadmap, business cases, governance pack and build plan.

Interactive

Try it on your own workflow.

Two quick tools to size up AI for your business before we talk.

Deliverables

What you keep.

  • Opportunity map and scoring model
  • Business cases with baselines and targets
  • Prototype code and test findings
  • AI policy and governance pack
  • Phased roadmap with estimates

Stack

Technology we work with.

Methods

  • Process mapping
  • Value-effort scoring
  • Design sprints
  • Cost modelling

Frameworks we reference

  • NIST AI RMF
  • ISO/IEC 42001
  • UAE PDPL
  • India DPDP Act

FAQ

Frequently asked questions

How long does a strategy engagement take?

It depends on how much of the organisation is in scope. A focused discovery on one function is short; an organisation-wide programme takes longer. We agree scope, timeline and deliverables before we start.

Do we have to build with you afterwards?

No. The roadmap and business cases are yours to use with any team. Many clients do continue with us, because the people who wrote the plan already understand the work.

We already have an AI pilot. Can you review it?

Yes. We assess what it would take to move it to production, covering data, integration, evaluation, security and running costs, and tell you plainly whether to scale it, rework it or stop it.

What do you need from us?

Access to the people who do the work, a sponsor who can make decisions, and read access to sample data and systems. We handle the rest.

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