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AI Strategy & Consulting

Know exactly where AI will pay off.

We help leadership teams cut through the hype: identify the highest-value AI opportunities, assess readiness and risk, and leave with a practical roadmap your teams can execute.

AI Strategy & Consulting

We don't stop at a demo. Every AI Strategy & Consulting engagement ships to production with evaluations, monitoring and documentation — measured against the outcomes that matter to your business.

Outcomes

What this means for your business

Prioritised opportunities

Use cases ranked by value, feasibility and risk — so you invest where returns are clearest.

Responsible adoption

Data privacy, security and governance considered from the start, not bolted on later.

A plan teams can run

A concrete roadmap with owners, milestones and success metrics.

What's included

Typical deliverables — tailored to your scope in our proposal.

  • Stakeholder workshops
  • Opportunity assessment
  • Data and technical readiness review
  • Build vs. buy recommendations
  • AI governance guidelines
  • Roadmap and business case

Example use cases

Common projects our clients start with.

AI opportunity workshopsBoard and leadership briefingsVendor and tool evaluationsAI policy and governanceProof-of-concept planningTeam upskilling

Typical technology

Chosen per project based on your requirements.

WorkshopsReadiness assessmentGovernance frameworksRoadmapping
How we deliver

From kickoff to launch

  1. Discover

    1–2 weeks

    We map your goals, users, data and constraints, then define the highest-value use case and how success will be measured.

  2. Prototype

    1–3 weeks

    A working prototype tests the riskiest assumptions with real data — so you see results before committing to a full build.

  3. Build

    4–10 weeks

    We engineer the production solution in short sprints with weekly demos, evaluations and full transparency on progress.

  4. Launch & scale

    Ongoing

    We deploy, monitor quality and cost, and keep improving — or hand over to your team with documentation and training.

Questions

Common questions

Something else on your mind? Ask us directly.

How long does it take to build an AI MVP?

Most MVPs take six to twelve weeks, depending on scope, integrations and data readiness. We agree milestones up front so timelines stay predictable.

Who owns the code and IP?

You do. All code, prompts, models, documentation and intellectual property created for your project are transferred to you.

How do you handle data privacy and security?

We follow least-privilege access, keep your data in your environment wherever possible, sign NDAs and DPAs on request, and use model providers configured not to train on your data.

How is pricing structured?

Discovery Sprints and MVP builds are fixed-price against an agreed scope. Dedicated teams are billed monthly. You'll receive a detailed proposal after our first call.

Let's talk about your AI Strategy & Consulting project.

Tell us what you're working on. We'll reply within one business day with honest advice on the fastest path to results.