AI is only as good as the data under it.
Everyone is being told to use AI. On messy data, it gives confident wrong answers. We fix the foundation first, so it's right.
Same question. Messy data vs. clean data.
On messy data
Waiting for a question…
On clean data
Waiting for a question…
Clean first
One matched set of numbers.
Your definitions
“Revenue” means what you mean.
Any AI tool
Ask in plain English today. Plug in more tomorrow.
Four ways messy data fools AI.
Each one is fixed before the first question is asked.
Counted twice
The same customer is in the CRM and in QuickBooks. AI adds them up and reports revenue 18% too high.
Duplicates merged before anything is asked.
Different names
“ACME Corp.” and “Acme Corporation” look like two customers, so your biggest account looks smaller than it is.
Names matched to one record.
No definition
Ask “what was revenue?” and get invoiced in one place, collected in another. Both sound confident.
Every number defined once, in writing.
Out of date
Last month's spreadsheet was the newest file it could find, so the answer is a month old.
Data updated on a schedule and checked for freshness.
Five levels, from scattered to AI-ready.
Click a level to see what it looks like and what it takes.
What it looks like: Real systems (QuickBooks, Procore, etc.) but they don't talk to each other.
What it takes: Connect and clean. The fastest payback.
Most companies we talk to are at level 1 or 2. Find your level in 5 questions →
Four things AI needs underneath it.
- 1
One clean database
Every source collected and matched, so there's one copy of the truth for AI to read.
- 2
Written definitions
“Revenue,” “job cost,” “active customer” — defined with you, once, and used by every answer.
- 3
Checks on every update
Bad rows are held back before AI or a person ever sees them.
- 4
The right access
Each person — and the AI answering them — sees only what they're allowed to.
Plain English. Real numbers.
Pick an industry and ask. Every answer comes from the sample records.
AI questions owners ask.
Do we need to buy an AI tool?
No. Ask Your Data comes with Workspace. Type a question in plain English and get an answer from your own numbers.
How do we know the answer is right?
Answers come from your cleaned database and the definitions we wrote with you, and they show the numbers they used. If a question can't be answered from your data, it says so.
Where does our data go?
It stays in your private database, separate from every other client. Ask Your Data runs there.
How long until we're AI-ready?
As long as Foundation takes to set up: about 2–10 weeks depending on size. You can start asking questions the day Workspace launches.
Can we use other AI tools on top?
Yes. Once your data is clean and defined, other tools can use it through the same access rules. We can set that up as Engineering work.