AI Enablement
We help you avoid customer data pasted into ChatGPT.
Your people already paste exports into ChatGPT to get through the week, and nobody can check what comes back or where the data went. We connect the AI tools you already pay for to your data model, set the rules on what they can see, and train each team on the questions that save them the most time. Your analysts then spend their week on insight and decisions.
Book a free discovery callFree 30 minute call with the engineer who would do the work. You keep the first fix whether or not you hire us.
Spreadsheets pasted into chatbots
Staff upload customer and finance exports to public AI tools because it is the fastest way to get an answer, and security finds out later.
Licences nobody uses well
You pay for Copilot, ChatGPT Enterprise or Gemini seats, and most people use them to rewrite emails because the tools cannot see your data.
Answers nobody can check
The AI gives a confident revenue figure with no query or definition behind it, so the numbers get argued over or quietly ignored.
AI your team trusts and uses every day
Connected to your data, governed and taught
We give your AI tools a governed route into your data through the semantic layer and MCP servers, so they answer from your own definitions and show their working. Access follows the permissions you already have. Each team leaves with the questions, prompts and habits that fit its job.
What you get
- Claude, ChatGPT, Gemini or Copilot connected to your data model
- Access controls and a log of every question asked
- Written rules on what data AI tools may touch
- Playbooks and training for each team
- A short list of the next workflows worth automating
What the engagement includes
Each engagement has a fixed list of deliverables, agreed before work starts.
AI readiness review
Which tools you pay for, how staff use them today, where data leaks out and which data is ready to connect.
Data connections
MCP servers and semantic layer access so AI tools query your defined metrics with the user’s own permissions.
Usage policy
Plain-English rules on what data goes where, agreed with security and legal, and set up in the tools themselves.
Team playbooks
The questions, prompts and checks that save each team the most time, written for finance, marketing, sales and operations.
Training
Hands-on sessions on real questions from your own business, so people keep using the tools after we leave.
Next workflows
Recurring reports and checks that are worth handing to an AI agent, ranked by time saved.
How the work runs
Review
See how AI is used today and where the risks are.
Connect
Give the tools a governed route into your data.
Teach
Train each team on its own questions.
This works best if
- You pay for AI tools and want more from them
- Staff already use AI with company data and you want it done safely
- You have a warehouse or plan to build one
Do we need a data warehouse first?
It helps a lot. AI tools answer best from a modelled, defined source. If yours is not ready, the readiness review says what to fix first, and we can fix it alongside.
Can the AI see data a person should not?
No. Connections run with each user’s own permissions, so the AI sees what that person could already see, and every question is logged.
How an engagement starts
The work runs in three steps. You see working output within weeks and can stop after any stage.
Discovery call
A 30 minute call with the engineer who would do the work. We look at your setup, tell you what we would fix first, and whether you need us for it.
Day 1Blueprint sprint
We map your sources, stakeholders and goals, then give you an architecture and a prioritised roadmap. You keep it whether or not we do the build.
2 to 4 weeksBuild in sprints
We ship working tracking, models, dashboards and agents every two weeks. You can stop after any sprint, and everything built stays yours.
Every 2 weeksWhat happens on the call
Book your call- 30 minutes with the engineer who would do the work
- No slides or sales pitch
- A clear answer on whether we can help, and a referral if we can’t
- The first fix we would make, which you can use either way