Problem
Every other vendor in this category sells you a service.
You have a question — which customers ordered last quarter but not this one, what this region’s pipeline looks like, whether that promotion actually moved anything. In most tools the path from your question to an answer runs through someone else: file a ticket, wait for IT, or call the vendor and get a quote. The person with the question is never the person who gets the answer.
Two whole categories grew up around that gap. The developer platforms — Retool, Power Platform — are powerful and priced for the IT department, not the operations head who actually has the question. The no-code tools — Zoho Creator, n8n — lower the skill bar but sit on whatever disconnected systems you already have, which for most mid-market companies is no real model at all. Either way, the chart is still three weeks and someone else’s sign-off away.
The line that matters
One question in a demo settled the whole pitch.
“So we can call you, and you build these dashboards for us?”
“No. You can do it yourself. Just describe what you need.”
That exchange is the entire pitch. AI Builder is built so the person who has the question is the person who gets the answer — no ticket, no developer, no sales call. You describe a view, a dashboard, a KPI, or a small automation in plain language, and the platform builds it on the live model and saves it where the rest of the team can use it.
Describe it, get it
You type a sentence. A working view comes back.
Not a starting template you still have to wire up. A real data view, built against the live model — the same customers, orders, and invoices the rest of the platform reads — and saved where your team can open it tomorrow.
No export, no spreadsheet, no “we’ll have it next week.” The view reads the live model, so the moment a customer reactivates they drop off the list on their own.
What you can build
Five things you build yourself, today.
Each starts with a sentence and ends with something saved on the live model — not a mockup, not a ticket. Scroll through.
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Data views.
Describe the cross-module slice you need — customers, orders, stock, anything on the model. It comes back as a live table you can save and share, not a static export.
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Charts and dashboards.
Say what you want to see — weekly revenue, top accounts, pipeline by stage — and get tiles with role-specific filters, saved into PA for repeat use.
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Suggested automations.
When a view surfaces a recurring problem, the platform proposes the rule that fixes it — and routes anything sensitive through Ticketing for a human to approve.
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Auto-generated KPIs.
Attach a KPI to any saved view in one step, with a target. It’s computed from the live model, not a snapshot — so it keeps counting after you close the tab.
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Saved into PA, today.
AI Builder isn’t a sidecar — it lives inside the PA module, on the same model as everything else. (UI Builder, extending it to any screen, is on the roadmap.)
Why it’s different
No-code creation, and a model the AI can actually reason over.
Two adjacent categories each solve half the problem. AI Builder is built on the bet that both halves matter at once — that’s what turns “describe an outcome” into a working surface instead of a starting template that still needs three weeks of integration.
- Who uses it
- The person with the question — in plain language
- Data underneath
- One live model — CRM, OMS, WMS, ERP, storefront
- Question → view
- Minutes
- KPI & sign-off
- Auto-generated; sensitive actions routed to Ticketing
- Who uses it
- IT — visual builder, but it needs technical skill
- Data underneath
- Whatever you connect — the model is your job
- Question → view
- Days to weeks — build queue + IT review
- KPI & sign-off
- Build it yourself
- Who uses it
- Lower skill bar — closer to the end user
- Data underneath
- Sits on disconnected systems — usually no real model
- Question → view
- Hours to days, plus integration work
- KPI & sign-off
- Limited
Who it’s for
Everyone — and that word does real work here.
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Department heads
Set the defaults and the governance — what the team sees, what’s shareable, what’s flagged for sign-off.
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Individual users
Customize within their own scope — their saved views, their dashboards, their KPI targets.
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Power users
Build cross-functional views no one had time to make by hand — joining CRM, ERP, and the storefront in one prompt.
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The CEO
Asks the question they’d have handed an analyst — and gets the chart, not a “we’ll have it next week.”
No “first you have to model your data” step. The model is already there. The only step left is the question.
Thesis
The person with the question should be the one who gets the answer.
The whole category decided that turning a question into a working view was specialist work — so it sold you the platform, then the build queue, then the consultant to staff it.
We started from the other end. If the model is already unified, the hard part isn’t the data — it’s the distance between the person who wonders and the person allowed to answer. Close that distance and the chart stops being a project. It becomes a sentence.
That only works because both halves are true at once: a no-code surface anyone can speak to, and a single model underneath that the AI can actually reason over. Take away either half and you’re back to a template that needs a developer, or a builder sitting on data that doesn’t connect.
The disproof line The bet is that the model is the moat, not the builder. If your data already lives in one well-modelled system and you have engineers who enjoy building internal tools, a developer platform will take you further than we will — and we’ll say so on the call before we sell you ours.
Bring a question you’d normally hand to an analyst.
Twenty-five minutes. Bring a real question off your own desk — a segment you keep rebuilding in a spreadsheet, a dashboard you’ve been waiting on — and we’ll describe it to AI Builder on your data and watch it come back as a working view. If the person with the question can get the answer, we talk pilot.