AI & data strategy
AI & Data Strategy Services
A roadmap that avoids the 88% failure rate.
Book a consultationMost AI strategies fail before any code is written — the wrong use cases get funded, the data isn't ready, and success is never defined. Our strategy work exists to prevent exactly that: an honest, evidence-based read on where AI will pay off for your business, what it will take, and in what order — from a team that also builds, so the plan is grounded in what actually ships rather than what looks good on a slide.
What we deliver
AI readiness assessment
A structured evaluation across data, technology, talent, process, and governance — where you're ready, where you're not, and what to fix first.
Use-case discovery & ROI ranking
Your candidate AI ideas turned into a ranked portfolio: expected value, feasibility, data readiness, and time-to-impact for each.
Implementation roadmap
A sequenced 6–12 month plan with owners, milestones, and the metric each initiative must move — built to survive contact with a budget review.
Data foundation review
Whether your data can support what you want to build — quality, access, and governance gaps identified before they sink a project.
Governance & compliance readiness
Practical AI governance: usage policies, risk classification, audit trails, and EU AI Act alignment scaled to your actual exposure.
Pilot rescue & vendor evaluation
A stalled pilot diagnosed and either fixed or retired; build-vs-buy decisions made on evidence instead of demos.
Where it delivers ROI
An AI roadmap the board can hold you to
A ranked, costed plan where every initiative has a number it must move — and a kill criterion.
A stalled pilot turned into a shipped system
A clear diagnosis of why it stalled and the shortest path to production — or an honest recommendation to stop.
Build vs. buy decided on evidence
A defensible recommendation grounded in your data, volume, and differentiation — not vendor promises.
How we work
- 1
Scope the value
We pin down the highest-payoff use case and the metric it should move.
- 2
Build to production
Senior engineers ship reliable software, not a throwaway proof of concept.
- 3
Deploy in your stack
It lands in the tools your team already uses, with guardrails you can trust.
- 4
Prove the return
We measure against baseline so the work shows up as an outcome.
Frequently asked questions
What does an AI readiness assessment involve?
Structured interviews and a hands-on review of your data, systems, team, and candidate use cases — typically two to four weeks — ending in a written assessment, a ranked use-case portfolio, and a recommended first move.
What do we actually get at the end?
Working documents, not a deck for a shelf: the readiness assessment, an ROI-ranked use-case portfolio, a sequenced roadmap with metrics and owners, and the business case for the first build.
We already have strong engineers. Why bring in strategy help?
It's rarely a talent gap — it's a selection and sequencing gap. Engineers are handed use cases; the expensive mistakes happen in which use cases get funded and how success is defined. That's the layer we fix, and we work with your engineers, not around them.
Will you tell us if AI isn't the answer?
Yes, and we regularly do. Some problems are process problems, some need plain software, and some aren't worth solving at current costs. Telling you that early is exactly what the engagement is for.
How does strategy connect to delivery?
The same firm that writes the plan can build the first system — so the roadmap is constrained by production reality from the start, and nothing gets lost in a handoff between an advisor and an implementer.
Related services
Custom AI Development
Production-grade AI software, built for your business.
AI Agents & Automation
Agents that take real work off your team's plate.
Ready to make it deliver?
Tell us what you're trying to do — we'll give you a straight read on feasibility and the fastest path to a return.
Book a consultation