We help your business understand itself.
Right now your business can't answer its own questions. What it knows sits in people's heads and in systems that don't agree, so every answer takes weeks and your AI just guesses. We put that knowledge into your data, so your people and your AI can act on it.
For leadership teams who want to move fast.
Your data exists. The meaning doesn't.
Most leaders start with the tools. Which model. Which copilot. Which agent. The answers stay thin, because the AI was trained on public data. It knows nothing about what makes your business different.
And you're the one explaining to the board why all that spend still can't answer a simple question.
- Finance, sales and operations each count customers differently.
- AI gets pointed at data nobody trusts.
- The report arrives too late to act on.
Fixing AI means fixing the context in your data.
We deliver the missing piece: the context layer. Four parts, in this order. Each one only works because the one before it does.
Agreed meaning
Before AI can answer anything, the business agrees what its words mean. What counts as a stock-out, an active shop, a loyal buyer.
Trusted data
We fix what's underneath: duplicates, gaps and definitions that don't agree. Every answer carries its source and its governance.
A shared picture
AI sees the business the way your leaders talk about it. Shops, orders, gaps, people, and what each is allowed to do.
Context for action
The chain, the history and the rules, so a decision runs as a closed loop: decide, act, check, learn.
You keep the systems you already have. We add the context on top of them.
We start with where you are.
Every engagement begins with one of three things. Bring whichever one is keeping you up at night.
- 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?
- What would we do differently if we rebuilt the business with AI?
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 actually 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 has already cost us?
- Which suppliers can we really rely on?
CIO
- Why can't the business get answers from the data platforms we've already paid for?
- How do we give AI our data without losing control of it?
- Which of our master data can we actually 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 actually move sales?
- Why does every report show a different number of customers?
- Where are we missing distribution we didn't know about?
CHRO
- Where will we be short of the skills we need in two years?
- Why do good people leave, and could we have seen it coming?
- Which teams are stretched too thin right now?
- How do we help our people work with AI instead of fearing it?
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 are really going to 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 workshopEveryone fixes the data. We make it useful.
Clean data is the starting line. We build on the data work you've already done.
Useful data understands your business.
It knows 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 |
Laying the foundation for an AI-native business.
You've spent a lot getting your systems and data in order, hoping it would finally get you AI and faster decisions. It stalls because the middle is missing.
That's where we start. We build the context layer first, so your AI finally has something to stand on.
Sooner or later, every business has to become AI-native to compete.
Execution layer
Where decisions get made and acted on. Your people, AI that helps them, and the result measured every time.
Context layer
This is where we startYour business, written down. What things mean, how they relate, the rules that apply and where every number came from.
Infrastructure and data
The systems you already run. ERP, CRM, spreadsheets, warehouses. We connect to them. Nothing gets ripped out.
Ten decisions to your competitor's one.
Most businesses run open loops. A decision gets made, and the result turns up weeks later in a report nobody connects back to it. So the next decision is no better than the last.
An AI-native business closes the loop. Every decision is measured, and the next one starts smarter. That's the value: more good decisions, made faster, each one better than the one before.
Open loop
Decide. Wait weeks. Guess what worked.
Closed loop
Decide. Act. Measure. Learn. Repeat.
From business problem to measured result. In weeks.
About a week from the first workshop to a signed proof of value. A measured result two to three weeks later. We don't try to boil the ocean. One decision, proved on your data, then the next.
About two hours
Use case workshop
Your executives agree the problem worth solving first and what success looks like in numbers.
Two to three days
See it working
A working mock-up on real or sample data, and an agreed scope for the proof.
Two to three weeks
Prove the value
A measured result on one use case, without disrupting the business.
Ongoing
Go live, add the next
Each new use case runs on the same foundation, so every one lands faster.
Your call at every gate: go, adjust or stop.
What you can hold us to.
Answers you can trust
One trusted picture of your business. Ask anything and the answer holds up.
Understanding in real time
Ask in plain language and get the same answer every time. If it doesn't know, it says so.
Change you can see
See what's shifting through your data as it happens, not in next month's report.
AI that acts, people in charge
Agents do the routine work. Your people handle the exceptions.
Your IP stays yours
Protected whichever way you host it, and never used to train anyone else's model.
What we've delivered.
Real work, on real data. Client names stay private.
Food wholesale
52 store systems, modelled in a week
A food wholesaler ran a separate system in every store. We modelled all 52 in a week, and attached 84 data-quality rules the week after.
Delivered by Streem AI
Banking
Collateral management for a tier-one bank
Collateral and risk data brought into one governed model. Data accuracy rose from 65% to 98%, delivery dropped from 10 months to 4 weeks, and more than 500 people use it in production.
Delivered by Infinity Data AI, on the capability we use
Informal retail
9,585 stores, verified at the shelf
A national study of informal-trade stores, every record checked in the field. It showed 61% of outlets didn't stock the brand yet, a gap nobody could see before.
Delivered by Streem AI
We work best with leadership teams running several systems that don't agree, who'd rather prove one thing in three weeks than plan for a year.
What's the one decision your business can't make right now?
Bring it to a two-hour use case workshop with your executives. We'll start with a short call to check it's a fit.