What we hear, most weeks
Everyone arrives with these four questions. The one that decides it is underneath them.
"Can AI do this?" has an answer now, and it's almost always a qualified yes — which means the question stopped separating the good ideas from the merely plausible ones.
"Help me polish the roadmap I already have."
The roadmap isn't the constraint. Which two items survive contact with your data is.
"How do we use AI to improve customer experience?"
There are eleven candidates in that sentence, and what a wrong answer costs differs by a hundredfold across them.
"How do we prioritise? What should we start first?"
This is the one. It's the question almost nobody asks first, and the only one whose answer saves money.
"Should we just build it? The build cost isn't that high."
You're right about the cost, and it isn't what decides. "Can we build this?" is usually yes. "Will we still be running it in three years?" is the question.
Underneath all four sits one question: what does a wrong answer cost, and who catches it? We answer it on your own data, read-only, in six weeks — before you commit to building anything.
In front of the AI already touching SAP, Oracle, Salesforce, Snowflake, Databricks, Shopify — and whatever else runs your business.
The arithmetic nobody does before signing
A 5% error rate is a full-time job you didn't hire for.
And that's the good case. It assumes you catch them. In personal use you read every output and you are the expert. At scale nobody reads them, and a wrong answer doesn't stop — it flows into a report, a decision, a customer conversation, a filing.
So the question isn't how accurate it is. It's what happens to a wrong one, and who catches it.
the quiet problem
The risk isn't what you don't know about AI. It's what you're sure of.
Your sense of what AI does came from using it — daily, for months, which is the most persuasive teacher there is. It is also a poor guide to what it does at your scale. The number that settles it was never in a demo. It's on your own data.
Watch mode
Before you trust it, watch it work.
An Inspector sits in front of the AI already running on your systems and keeps the record. It filters what breaks your rules before the model sees it, reconstructs what arrives malformed, and detects the mismatches nobody logged. Read-only, touching nothing, inside your own walls. One real pass, recorded.
See a Watch-mode recordWhy checkLLM
The mess is the reason.
SAP and Oracle. Salesforce and Shopify. Snowflake and Databricks. Decades of legacy and a pile of new SaaS — and now AI is touching all of it. We don't ask you to replace any of it. We put proof around the AI that already runs on it.
Tame what you can't rip out
The systems that run your business are too critical to replace. We govern the AI touching them instead.
Not one more AI tool
We're the layer above the tools you already have — rules, safety and a clear record. Not another pile to manage.
The work a chatbot can't touch
Private, regulated, high-sensitivity work, run inside your own walls, where a general assistant is never allowed to go.
One standard, two ways to get it
Inspectors are the fastest path where they fit. Where they don't, our team builds custom on the same provable standard.
Trusted by stringify ai, checkLLM inherits the same provable standard — sourced, governed, on record. We build the layer that lets you move at AI's speed and still sleep, on your own terms, wherever you run.
From the founder
You cannot talk someone out of a belief they formed through experience. You can only give them a better experience.
portraitgopal-joshi-avatar.jpg
The trust ladder
Land read-only. Earn every step.
You don't hand autonomy to an AI on day one. An Inspector starts by watching, and only moves up as it proves itself.
It observes and reports. Touches nothing — just shows what it would have caught.
It proposes each fix, and a person signs off before anything runs.
Once trust is earned it acts on its own — still logged, still inside your walls.
Proof, not promises
Don't take our word for it. Watch an Inspector on your own stack.
We're early, and we'd rather show than tell. In Watch mode an Inspector observes your real environment at zero risk and shows exactly what it would have caught — the proof writes itself. We describe our posture in facts, not badges.
A Watch-mode record — quiet, on your infrastructure, nothing run.
Design partner program
Now onboarding partners in regulated sectors.
Help shape the product, get early access on your own stack, and grow with us as a founding partner.
What an Inspector won't do
Four things we'd rather tell you now.
It won't tell you whether the use case was worth doing.
It tells you what it costs when it's wrong, and who would catch it. That is a smaller claim than this category usually makes, and it is the one we can keep.
It won't fix data you can't reach.
If the access isn't there, Watch mode tells you in week one. That's an uncomfortable finding, not a deliverable — and it's where most enterprise AI projects quietly die, in month three, in a room with the security team.
It won't catch what nobody defined as wrong.
Your rules are the ceiling. An Inspector enforces the policy you can state. It does not discover the policy you haven't written.
It won't survive an owner leaving.
When the model underneath is deprecated and the person who configured it has moved teams, someone has to own it. If you can't name them for month nine, price in a rebuild.
And most of your ideas shouldn't be built.
We would rather find that in six weeks than help you build the other nine. It's a smaller sale and a much better one.
Let's talk — a demo is rarely the first step.
Tell us what you're running and what's on your mind. We'll point you to the right next move — an intro, a demo, or just an honest answer. No wasted time, yours or ours.
or email checkllm@stringifyai.com
From the field
Recognize the work. Then see it made provable.
on the record · Sep 2026
Confidence is the new bottleneck
Ten years in enterprise AI pre-sales — the technical chair, not the selling one — and what replaced the education problem. Literacy got solved. Permission inverted. Calibration got worse, and that is now the expensive one.
case-study · Feb 2026
The invoice bot was sending SSNs to the model
An ordinary SAP invoice-extraction step was quietly passing two PII fields to the model. Here is what an Inspector caught in Watch mode, at zero risk.
on the record · Aug 2026
Copilot is licensed. That doesn't mean it's governed.
A Copilot licence is a buying decision, not a governance one. The gap between having Copilot and proving what it touched is where the risk lives.