AI Consulting & Strategy

Honest, evidence-driven AI strategy. Readiness audits, opportunity mapping, ROI modelling, and build-vs-buy reviews — done by engineers who ship, not just slide decks.

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AI Consulting

AI strategy that survives contact with reality.

A pragmatic plan tied to outcomes you can measure, with a build-vs-buy answer for each opportunity.

Common signs your team is overdue for ai consulting:

  • Glossy roadmaps with no eval criteria or guardrails
  • Build decisions made before anyone tried the off-the-shelf option
  • “AI strategy” that ignores data quality, change management, and cost
  • Initiatives optimized for headlines, not outcomes

What we build for ai consulting:

  • AI readiness audit (data, talent, infrastructure, risk posture)
  • Opportunity mapping: ranked list with effort, impact, and risk
  • ROI models tied to your real cost and revenue numbers
  • Build-vs-buy review per opportunity, with reference vendors
  • 12-week roadmap with milestones, evals, and exit criteria
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Capabilities

When to bring us in

Pragmatic plans tied to outcomes — outcomes our clients keep coming back for.

Before committing budget

Pressure-test the opportunity before you sign the contract or hire the team.

Looking for the right starting point

Find the lowest-risk, highest-leverage AI use case to ship first.

Build vs. buy

A clear answer for each capability — with TCO, vendor list, and risk.

Mid-flight course correction

Honest review of in-progress AI work — what to keep, what to stop.

How we deliver

Two-week consulting sprint

01

Discover

Workshops with leadership, ops, and engineering. Look at real data and processes.

02

Audit

Score readiness across data, talent, infra, governance.

03

Map opportunities

Long-list, score on impact / effort / risk, shortlist top 5.

04

Plan

A 12-week roadmap with measurable milestones and exit criteria.

Tools & platforms we use:

Workshops Stakeholder interviews Data audits Opportunity scorecards TCO models Vendor reviews Risk registers Roadmaps

FAQ

Questions teams ask us about AI Consulting

How is this different from a Big-Four consulting deck?
Our consultants are engineers who ship. Every recommendation is something we’d be willing to build — and many of them, we end up building.
What deliverables do we walk away with?
A readiness scorecard, ranked opportunity map, build-vs-buy decisions, ROI models, risk register, and a 12-week roadmap.
How long does it take to get to production?
Most projects ship a real, usable system in 3–6 weeks. Discovery is 1–2 weeks; build sprints are weekly with demos.
Will my data be used to train models?
No. We default to enterprise tiers (OpenAI, Anthropic, Bedrock, Vertex) that don’t train on your data. For sensitive use cases, we deploy open-weight models on your infrastructure.
How do you control costs?
We design cost-aware from day one — model routing (cheap model first, escalate when needed), caching, batch processing, and per-user budgets with alerts.
Can you work with our existing engineering team?
Yes. We embed alongside your team, transfer ownership progressively, and document everything we build.