Turn AI ambition into a funded, measurable roadmap.
We audit your data, processes, and systems, then rank the AI opportunities by business value so your first investment pays for the next one.
Most AI programmes stall because they start with a tool rather than a business problem. We start the other way around, with the processes that cost you money, the decisions that take too long, and the data you already own.
Our consultants combine enterprise delivery experience across Salesforce, ERP, and custom engineering with hands on machine learning practice, so the recommendations you get are buildable inside your current systems and budget.
You finish the engagement with a ranked backlog, an architecture direction, a governance model, and a first build scoped to prove value in weeks rather than quarters.
What we deliver
AI Consulting and Strategy capabilities.
AI opportunity assessment
Workshops with your operations, sales, finance, and technology leads to surface where AI removes cost, delay, or risk.
Data readiness review
An honest assessment of the data you hold, its quality and lineage, and what must be fixed before models can be trusted.
Value and ROI modelling
Each use case is sized on effort, expected benefit, payback period, and the risk of doing nothing.
Reference architecture
A target architecture covering models, data platform, integration, security, and cost control across cloud providers.
AI governance and policy
Acceptable use, human oversight, model review, audit logging, and compliance mapping for regulated industries.
Pilot definition
A scoped first build with clear success metrics, so you can decide to scale on evidence rather than opinion.
How we work
A short path from idea to production value.
-
01
Discover
Interviews and process walkthroughs across the functions where AI could matter most.
-
02
Assess
Data, systems, and skills assessment against each candidate use case.
-
03
Prioritise
A ranked roadmap with cost, benefit, effort, and sequencing agreed with your leadership.
-
04
Prove
We build the first pilot and measure it against the business metric we agreed up front.
Business outcomes
What changes for your business.
-
A roadmap you can fund
Costed, sequenced, and tied to business metrics your finance team recognises.
-
Fewer dead ends
Use cases with weak data or unclear value are ruled out before they consume a budget.
-
Governance from day one
Policy, oversight, and audit built into the plan rather than retrofitted after a rollout.
FAQ
Questions we are asked most.
How long does an AI audit take?
Two to three weeks for most enterprises. Larger multi-entity organisations take four to six weeks, usually because data sits in more systems.
Do we need clean data before starting?
No. Part of the audit is telling you exactly which data is usable today, which needs remediation, and which use cases can proceed regardless.
Will you recommend building or buying?
Both, honestly. Where a licensed product solves the problem well, we say so. We only recommend custom builds where they create durable advantage.
Who should attend from our side?
A business sponsor, process owners from the functions in scope, a data or IT lead, and someone from risk or compliance if you are regulated.
How the work runs
A delivery rhythm you can plan around.
Discover
Workshops to map processes, systems and the outcome you are measured on.
Design
Solution blueprint, data model and delivery plan agreed before we build.
Build
Two week sprints with working software and a demo at the end of each one.
Launch
Migration, UAT, enablement and a cutover plan your teams can rehearse.
Support
Managed support, enhancements and quarterly roadmap reviews.
More AI services.
AI practice overviewGenerative AI and LLM Applications
Assistants, copilots, and document intelligence built on your own knowledge, with grounding, evaluation, and guardrails.
ExploreAI Agents and Intelligent Automation
Agents that take real actions across your systems, with approvals, audit trails, and safe fallbacks.
ExploreData Engineering for AI
Pipelines, warehouses, and vector stores that make enterprise data usable, governed, and ready for models.
ExploreReady to put AI to work on a real business problem?
Bring us one process, one dataset, or one question. We will tell you honestly whether AI is the right answer and what it would take to build.