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The whole idea, in one page

Your AI. Over everything.
Your data never leaves.

Keep the model you already trust — Claude, GPT, Gemini. It turns your question into a precise query and hands it to your box. Your box answers over every record — exact, and cited to the record — and gives it back. The model never sees a single record.

Two ways to do it

One reads your data. One asks a question of it.

Every “AI over your data” tool makes a choice about where your records go. That choice decides what it costs, what it can answer, and whether your data ever leaves your building.

The usual way

Pour your data into the model

  • It can only read a slice at a time — and guesses about everything past it.
  • It can’t tell you which record the answer came from.
  • Your records sit in someone else’s context to get an answer.
  • The bill grows with every record you keep — until it won’t fit at all.
Our way

Your AI writes the question

  • The box answers over every record — never a sample.
  • Every answer is cited to the exact record, with a receipt you can re-check.
  • The model sees the schema and its own query — never a record.
  • The cost is flat, whatever you hold — and falls when a question repeats.
What you can finally ask

The everyday gets faster. The impossible gets answered.

The questions a person actually asks — and the ones you could never trust an AI with, because they have to be right across everything.

The everyday
“What’s the margin on job 100042?” “Show me every open work order on the Dallas account.” “Which invoices are past 60 days?”
The ones that were impossible
“Across all four million records, which ones break this rule?” “What’s our total exposure — counted over everything, not a sample?” “Does any agreement auto-renew in the next 90 days?”

Each answer comes back with the exact records it rests on — and a receipt anyone can re-check. It never guesses over a handful and hopes.

The difference, measured

Your bill stops growing with your data.

You send the question, not the records — so asking a hundred million records costs about what asking a thousand does.

483
Tokens to answer — flat, whether you hold a thousand records or a hundred million.
152,497×
Fewer tokens than reading your data into the model, at a million records — and climbing with every record you add.
< 0.1 s
To answer over a million records — every one of them, cited, never a sample.

See the difference, measured →

See it for yourself

Not slides. Working demonstrations.

Each one is a claim proving itself on real records, right in your browser. Nothing leaves the box.

🧠

Ask your data

Point your own Claude or Gemini at 44,000 records. It writes the query; the box answers exact and cited.

Open →
📊

The token math

Watch the cost of asking stay flat as the data grows — while reading it all in runs off the chart.

Open →
⚖️

The bake-off

Same questions, same records: read-a-sample vs answer-over-every-record. Bring your own AI and run it.

Open →

Answer cold

Race a decade-old record against a fresh one — both answered exactly, both cited.

Open →

Rewind

Slide a work order back through every version it ever had, and prove each step.

Open →

Prove it

Edit a sealed certificate and watch the receipt stop verifying. Tamper never hides.

Open →

See the full set →

See it on your own data.

Every claim here is something we can show you running — on a slice of your own records, no slideware. Tell us what you keep, and we’ll set up a look.

© Validiti · records you own, proof built in Home · See it live · contact@validiti.com