AI Acceleration
You can't decide when your data means four different things.
We map how it connects, so your people and AI work from one answer they can act on.
One decision at a time, on the data you already have. A measured result in weeks.
For leaders who've tried to make AI work, and seen it stall.
Your data exists. The meaning doesn't.
What waiting costs you
You've done the work. You cleaned the data, picked the tools and bought the software.
But your smartest AI model still knows nothing about your company. So it guesses faster.
Your data is fixed. It still isn't useful.
Now you're the one explaining to the board why all that spend still can't answer a simple question. It shouldn't take three weeks and five people to get one.
- Finance, sales and operations each count a customer differently.
- Your best people spend the week agreeing on the number, not on what to do about it.
- A competitor makes ten decisions to your one, and the gap keeps growing.
Fixing AI means fixing the context in your data.
The missing piece is the context layer. It has four parts, built in this order, and each one needs the one before it.
Agreed meaning
Before AI can answer anything, the business agrees what its words mean. What counts as a customer, a stock-out, an active shop, a loyal buyer.
Technically: semantic definitionsAnswers you can trace
We find where the numbers sit, and what each key word means in each system. Every answer shows where it came from.
Technically: data lineageA shared picture
AI sees the business the way your leaders talk about it. Shops, orders, gaps, people, and what each is allowed to do.
Technically: an ontologyContext for action
Your AI knows the chain, the history and the rules. So the person who owns the decision can make the call with an answer they can act on.
Technically: governance and rulesYou keep the systems you already have. We map how they connect.
See the three layers under every fast decisionDecisions accelerate when your data means one thing.
Everyone works from the same number.
Finance, sales and operations stop arguing about whose figure is right. Ask a question, and the answer holds up.
Question your data in plain English.
Ask AI the way you'd ask a colleague. Same question, a deeper answer that uncovers the hidden patterns in your data.
Track the changes that happen daily.
See the drift of your business through your data. Track what's changing every day to align to strategy and stay in compliance.
AI does the legwork. People make the decision.
Agents take on the routine work, in pilot with design partners today. Your people handle the exceptions and make the strategic decisions.
What you build stays yours.
Your data and IP stay inside your business, not with the AI model providers. Protect your competitiveness!
We start with where you are.
Every engagement starts with one of three things. Bring the one that's costing you most.
- The question you can't answer
- The outcome you can't deliver
- The decision you can't make
Pick your seat at the table. Here's where leaders like you usually start.
CEO
- Which parts of the business are growing, and which are quietly losing money?
- Why does it take three weeks to answer a question I asked on Monday?
- Where should we use AI first to make a real difference?
- Why does every big decision end up waiting on my desk?
CFO
- Where is our cash across the group, and is it working hard enough?
- Why don't finance, sales and operations agree on the same number?
- Which customers and products make us money?
- How confident are we in this quarter's forecast?
COO
- Where are we losing time or money that nobody can see?
- Which sites, stores or routes are underperforming, and why?
- Why do we only hear about a problem once it's already cost us?
- Which suppliers can we rely on?
CIO
- Why can't the business get answers from the data systems we've already paid for?
- How do we give AI our data without losing control of it?
- Which of our master data can we trust?
- How do we prove an AI use case without a two-year programme?
CMO
- Which customers are we about to lose?
- Did our last campaign move sales?
- Why does every report show a different number of customers?
- Where are we missing distribution we didn't know about?
Risk and compliance
- Can we show an auditor where every number came from?
- Which customers or transactions carry risk we're not seeing?
- How do we stay in control once AI starts making recommendations?
- Are we applying the same rules in every system?
Sales
- Which accounts are growing, and which have gone quiet?
- Where is pricing quietly costing us volume?
- Which deals will close this quarter?
- Which customers should we be talking to this week?
Bring the question. We'll find the data it needs. See the solution for every role
Book a use case workshopName it. Prove it. Run it.
From stalled decision to measured result, in weeks. About a week from the first workshop to a signed Proof of Value. A measured result within four weeks after that.
Name it
About two hours
Use case workshop
Two hours with the executives who own the problem. You agree the one decision worth solving first, and what success looks like in numbers.
Prove it
Up to five days
Proof Point Accelerator
A working mock-up on a slice of your data, and an agreed scope for the Proof of Value.
Prove it
Up to four weeks
Proof of Value
A measured result on one decision, without disrupting the business.
Run it
Ongoing
Live into production
The proven decision in daily use. The Value-Accelerated Team takes on the next one, on the same foundation, so it lands faster.
Your call at every gate: go, adjust or stop.
Move a stalled decision or unsolved outcome to a measured result in weeks. You don't move a thing, and we prove it before you commit.
Everyone fixes the data. We make it useful.
Most data projects try to boil the ocean. They clean everything, land it in a warehouse and make it available. Where they finish, we start. We build on the data work you've already done.
Useful means one answer you can act on.
We map what a customer is, how stores, products and money relate, and where every number came from. That's what AI needs before anyone can trust it.
| Fixed data | Useful data |
|---|---|
| Clean, complete and in one place | Knows what it means and how it connects |
| Tells you what's in the table | Helps you decide what to do next |
| Each system still has its own definition | One agreed definition everyone uses |
| Needs a technical person to query | Anyone can ask a plain question |
| Ends at a tidy warehouse | Starts at the decision |
What we've delivered.
Trusted by tier-one companies. Real work, on real data. Client names stay private.
Each of our four founders has more than 30 years in business.
Food wholesale
Every store on its own system, joined up
A food wholesaler ran a separate system in every store, and none of them agreed on a product code. We mapped how they all fit together, then attached the core data quality rules.
Head office can now ask one question and get one answer. Nothing was migrated or replaced.
Delivered by Streem AI
Banking
Collateral answers in minutes, not days
A major bank held its collateral across several systems. Asking how much a client could borrow took days of work across teams.
Now the answer comes back in minutes, with current valuations, the right haircuts and a full audit trail. It runs live, on the bank's own systems.
Delivered by Infinity Data AI, the tooling we use
Bring us the decision that's waiting on your data.
You know the one your exco keeps putting off. Two hours with the executives who own the problem is enough to name it. We'll start with a short call to check it's a fit.
We build AI-native businesses with leaders driving change.