Production AI, engineered end to end, six eval-gated service lines.
The same playbook, tuned to the constraints of the sectors we ship into most.
Proof, not promises, selected case studies and recognition.
A transparent, 3-phase playbook from first audit to embedded team.
The senior team behind the work, and how to reach us.
Commit budget to AI with a number behind the decision, not a hunch. Our strategy sprints, architecture audits, and build-vs-buy memos quantify the opportunity, the cost, and the risk, so you and your board move forward with confidence. We can build it afterward, or hand the plan to your team.
Strategy before code. Every engagement produces a written, numbered deliverable not slide decks and verbal recommendations.
A two-week sprint that produces a written AI roadmap: prioritised use-cases, build-vs-buy recommendations, data readiness assessment, and a 90-day action plan.
A thorough review of your existing AI system model selection, eval coverage, infrastructure reliability, and security posture with a prioritised remediation plan.
Rigorous financial and technical analysis comparing custom builds against SaaS vendors and open-source options. We model the 3-year TCO, not just the sticker price.
Evaluate your data infrastructure, engineering team capacity, and organisational readiness before committing to an AI build. We tell you what's missing and how to fix it.
Model bake-offs on your actual data and use-case. We run the evals, present the results, and make a written recommendation backed by numbers, not vendor marketing.
Hands-on workshops and pairing sessions to bring your engineering team up to speed on LLM engineering, RAG, and eval-first development. Knowledge transfer, not dependency.
Our consultants are senior AI engineers who have shipped production systems. When we tell you something is feasible, we've built it before. No inflated promises from people who've never written a line of inference code.
Every consulting engagement ends with a written document: a memo, a roadmap, or an audit report. Something you can act on, share with your board, and revisit six months later.
We tell clients when rules-based systems are better than AI, when their data isn't ready, and when the risk profile doesn't justify autonomy. Honesty protects both of us.
We recommend tools because they're the right fit, not because we have a reseller agreement. Our analysis compares vendors on your requirements, not their marketing budgets.
Yes this is our most common consulting entry point. We run a two-week AI Strategy Sprint that maps your business processes, identifies where AI creates the most leverage, and gives you a prioritised roadmap before any code is written.
Absolutely. We do independent technical reviews of vendor proposals and SaaS AI products. We check the claims, run the evals, and give you an honest second opinion before you sign a contract.
A written memo covering: total cost of ownership over 3 years (custom vs. vendor), capability gap analysis, integration complexity, data sovereignty implications, and a final recommendation with the reasoning shown. It's the document you take into your board meeting.
Typically two weeks for a scoped system. We review your model serving, eval coverage, data pipeline, security controls, and observability, then present a prioritised finding report with severity ratings and remediation steps.
30 minutes, one of our seniors, no slide deck. By the end of the call you'll know whether we're the right team, and if not, who is.