AI Consulting Services
AI advice from the people who build the system.
We assess where AI is genuinely worth the money, test whether your data supports it, and hand back a costed roadmap with architecture, evaluation plan, and staged milestones — not a slide deck.
Assessment
2-3 weeks
From kick-off to a prioritised, costed roadmap
First pilot live
4-6 weeks
Working system, not a prototype demo
Team
Senior only
The engineers who advise also build
Deployment
Cloud or VPC
Enterprise and government-ready architecture
What an engagement covers
Opportunity assessment
We interview the people doing the work, quantify the current baseline, and rank opportunities by value, feasibility, and the cost of being wrong.
Data and readiness review
An honest look at the data you actually have: coverage, quality, access paths, labelling needs, and the gaps that would sink a naive pilot.
Build vs. buy analysis
Per use case: extend an existing product, buy a platform, or build. With lock-in, integration effort, and exit cost stated explicitly.
Architecture and evaluation plan
Target architecture, model and vendor selection, and the eval harness that will tell you whether the system is good enough to ship.
Cost and ROI modelling
Token, infrastructure, and operating cost per transaction at realistic volume, set against the manual cost it replaces.
Security and compliance guidance
Data residency, PII handling, access control, audit requirements, and human-in-the-loop checkpoints designed in from the start.
Why teams bring us in
AI strategy for a leadership team
Turn a long list of competing AI ideas into a ranked, costed roadmap the board can approve and engineering can start on Monday.
Vendor and platform selection
Independent evaluation of AI vendors against your real requirements, data constraints, and total cost over three years.
Rescuing a stalled pilot
Diagnose why a proof of concept never reached production — data, evaluation, architecture, or ownership — and lay out the shortest route out.
Government digital services
Feasibility, procurement-ready specifications, and auditable architectures for public-sector AI programmes.
Engineering-led consulting vs. advisory-only firms
| Dimension | Premium Robots | Advisory-only firm |
|---|---|---|
| Deliverable | Executable build plan | Strategy deck |
| Who advises | Engineers who ship | Analysts who hand off |
| Data reality check | Sampled and tested | Assumed |
| Cost model | Per-transaction, at volume | Licence estimate |
| Follow-through | Same team implements | New vendor search |
Frequently asked questions
- What is AI consulting?
- AI consulting is the work of deciding what to build before you build it: which processes are worth automating, whether your data supports the idea, what the architecture and running cost look like, and how success will be measured. The output is an executable plan, not a slide deck of vendor logos.
- What does an AI consultant actually deliver?
- A prioritised opportunity register with effort and value estimates, a build-versus-buy recommendation per opportunity, a target architecture, a data and security review, an evaluation plan, staged delivery milestones, and an operating-cost model you can defend in a budget meeting.
- How do we evaluate AI consulting firms?
- Ask for a system they built that is still running in production, who operates it now, how quality is measured, and what it costs per month. Firms that only present strategy work cannot answer those questions. We are an engineering company that consults, so the plan we write is one we can also implement.
- What are good alternatives to large AI consulting firms?
- A small senior team that builds as well as advises. You get direct access to the engineers making the decisions, a shorter path from assessment to a working pilot, and no layers of billed juniors between the strategy and the code.
- Is hiring an AI consultant worth it for a small business?
- It is when the wrong choice is expensive: a rebuilt integration, a licence you cannot escape, or a model that fails on your data. For smaller teams we run a compact two-week assessment that ends with one prioritised pilot rather than a full transformation programme.
- How long is a typical engagement?
- A focused assessment runs 2-3 weeks. A full strategy plus reference implementation of the first use case runs 6-10 weeks, after which your team can continue independently or we keep delivering.
Book an AI assessment
Tell us the process you want to improve and we will come back with a scope, a timeline, and the questions we need answered first.