What this solves
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Understand exactly where AI moves the needle in your business — before you spend a pound on implementation.
Most AI projects fail before they start: wrong problem, wrong tool, no internal buy-in, no measurable definition of success. We fix that first.
Get a quote Typical timeline: 2–4 wks
Process
How it works
01
Discover & Map
We audit your current processes and identify the highest-impact automation opportunities.
02
Design & Build
The consulting engagement exists because we've seen too many businesses spend six figures on AI implementation that delivers nothing — usually because the discovery phase was skipped or done badly.
03
Monitor & Optimise
Your automation ships with monitoring, alerting, and a handover pack. We stay available for optimisation.
What's included
The consulting engagement exists because we've seen too many businesses spend six figures on AI implementation that delivers nothing — usually because the discovery phase was skipped or done badly. Our structured operational audit gives you a granular, ROI-ranked map of AI opportunities in your specific business, an honest assessment of the tools and approaches that fit each one, and a sequenced implementation roadmap you can execute — with us or internally. Engagements close with a working proof-of-concept on your highest-priority opportunity so there is a tangible output, not just a PowerPoint.
What you receive
- Pre-engagement questionnaire and system access checklist for rapid onboarding
- Operational audit — structured interviews with 5–10 process owners across your business, observation of key workflows
- Process inventory with time-and-cost estimates for each manual activity that is a candidate for automation
- AI opportunity register — each opportunity scored on ROI potential, implementation complexity, data readiness, and strategic alignment
- Tool landscape assessment — for each opportunity, a shortlist of tools evaluated against your stack, team capability, and budget
- Proof-of-concept build on the top-ranked opportunity (within the engagement timeline)
- Implementation roadmap — phased, with effort estimates, dependency sequencing, and go/no-go decision points
- Executive summary presentation for leadership sign-off
Typical outcomes
- Clear, prioritised map of AI automation opportunities — ranked by estimated ROI, implementation complexity, and time-to-value
- Honest "build vs. buy vs. configure" recommendation for each opportunity, with specific tool shortlists
- AI readiness assessment — data quality, system integration feasibility, and organisational change requirements for each opportunity
- Proof-of-concept on the highest-priority use case, demonstrating feasibility with your actual data
- Business case document for internal sign-off — estimated cost, projected saving, and payback period per initiative
- Sequenced 12-month implementation roadmap with dependencies, resourcing requirements, and decision gates
Technology we use
Ready to discuss your project?
Book a free sessionIntegrations
Tools & integrations we work with
N8NOpenAI GPT-4oAnthropic ClaudeLangChainPythonHubSpotZapierMakeAzure OpenAIAWS Bedrock
We integrate with your existing stack — no rip-and-replace required.
Questions
Common questions about AI Operations Consulting.
Every engagement closes with a working proof-of-concept — actual code running against your data, not a wireframe. The roadmap is also costed and sequenced as a genuine implementation plan, not a list of suggestions. If you're working with us, the next step after this engagement is execution, not another discovery phase.
Failed AI projects almost always have a traceable root cause: wrong problem framing, data that wasn't ready, a tool chosen for novelty rather than fit, or no clear success metric. We start the audit by understanding what was attempted and why it didn't work. That diagnosis directly shapes the opportunity prioritisation and the guardrails we put on the roadmap.
We need structured time with the people who do the work — typically 45-minute interviews with 5–10 process owners. We also need read access to the systems that run the processes being audited (to understand data quality and integration feasibility), and a sample of the documents or data involved in candidate automation use cases. We do not need production system write access or access to sensitive customer data at this stage.
The tools are generic; the application is always specific. We've worked across logistics, professional services, healthcare administration, construction, financial services, and manufacturing. The audit is designed to surface the specifics of your operation, not apply a template. The proof-of-concept is built on your data and your processes, which is why it's a genuine feasibility test rather than a demo.
That's a legitimate outcome and we design the deliverables accordingly. The opportunity register, tool assessments, and implementation roadmap are written to be executable by a capable internal team or a different implementation partner. You retain all deliverables. If the audit surfaces opportunities you want to build with us, we scope those as separate fixed-price engagements.