AI Consulting & Strategy
AI advice from people who build, not decks.
Most AI strategy fails at the same spot: the gap between the slide and the system. Our consultants are the engineers who would be accountable for making it real, so the advice survives contact with production.
How we help
Use-case discovery & prioritization
A structured sweep of your workflows to find where AI genuinely pays, scored by feasibility, ROI and risk, with the unviable ideas killed early and explicitly.
Architecture & vendor review
Second opinions on proposed AI architectures, model choices and vendor pitches. We've seen what breaks; we'll tell you before you sign.
Build vs. buy decisions
An honest analysis of when an off-the-shelf tool is enough and when custom is worth it, including the answer consultants hate giving: don't build this.
AI roadmaps & pilot design
A sequenced plan from first pilot to production platform, with eval criteria defined up front so success isn't a matter of opinion.
What you get that generic consultancies don't have
Frontier-lab calibration
Our engineers worked on projects for OpenAI and Google during their time at Turing. We know what state-of-the-art actually looks like, and what's marketing.
Numbers, not adjectives
Every recommendation comes with a cost model covering tokens, infrastructure and people, plus an eval plan. If a proposal can't be measured, we don't make it.
Implementation-ready output
Deliverables are written for the engineers who build next: architecture docs, data requirements, risk registers, eval specs. No 60-slide decks that die in a drive.
Skin in the game
We're happy to be held to our own advice. Many consulting engagements convert into us building the thing we recommended, at the price we estimated.
Typical engagements
- 2-week AI opportunity assessment for a leadership team
- Architecture review before a major AI vendor contract
- Rescue review of an AI project that isn't converging
- Data-readiness audit before an ML or RAG initiative
- Fractional AI-lead support for a growing engineering team
FAQ
Questions we hear a lot
Who is AI consulting for: startups or enterprises?
Both, with different shapes. Startups usually need architecture and build-vs-buy decisions made fast and cheaply reversible. Enterprises need feasibility, compliance and integration mapped before committing budgets. We run both playbooks and price them differently.
What does an engagement look like?
Most start with a fixed-scope, fixed-price assessment of 2 to 4 weeks: interviews, systems review, use-case scoring, and a written plan with costs and eval criteria. From there you can build with us, build in-house against our spec, or stop. The deliverable stands alone either way.
Can you review work from another vendor?
Yes. Architecture reviews and project-rescue assessments are a significant share of our consulting work. You get a written, evidence-based read on what's sound, what's fragile and what it would take to fix, which you can share internally or with the vendor.
Do you only recommend solutions you would build?
No. When an off-the-shelf product, a simpler automation or doing nothing yet is the right answer, that's the recommendation. Our consulting is only worth buying if it's independent of our delivery pipeline.
How do you price consulting?
Fixed price for fixed-scope assessments, weekly rates for embedded advisory. You'll know the number before we start. We don't do open-ended discovery billing.
From our writing
How to Choose an AI Development Company: 12 Questions That Expose Slideware
A practical guide to how to choose an AI development company: 12 direct questions on technical fit, real delivery proof, security, MLOps, and pilot terms.
Why AI Pilots Fail to Reach Production (and How to Design One That Won't)
Most corporate AI pilots die between the demo and deployment. The causes are predictable and mostly avoidable. Here are the five failure modes we see, and a pilot design that dodges them.
What Makes an AI System 'Agentic'? A Plain-English Guide for Decision-Makers
Agentic AI is the difference between software that answers and software that acts. Here's what the term actually means, why agents are hard to build, and how to tell whether your business needs one.
Ready when you are.
Tell us what you're working on. You'll get an honest read on feasibility, timeline and cost.