Secured and grounded AI,at enterprise scale.
Jubi reads your dashboards, respects your policies, and never invents your numbers. Studio is what people use. Guardian is what enforces every request. Atlas is what it knows.
"AI on your data" sounds simple. Three things kill the pilot.
Most enterprise AI pilots make it through a demo. Most don't make it through procurement, audit, or finance review. The cost of getting it wrong is already showing up in public.
Across these incidents, three patterns repeat. Each one is what kills the next pilot.
The AI sounds right. The numbers don't match the dashboard.
A finance lead asks for last quarter's gross margin. The model infers it from column names and returns 62%. The verified figure is 54.7%. Nobody catches it until the board deck has already shipped.
- ·No grounding to verified, named metrics
- ·No source attached to any number returned
- ·No replay when an answer looks off
- ·Confidence in tone, not in evidence
The warehouse knows who can see what. The summary AI doesn't.
A junior analyst asks "who are our top customers this quarter?" The query layer would have refused — they aren't entitled to customer PII. The AI obliges with a friendly summary that includes names, contract values, and contacts.
- ·Field-level permissions don't reach the model
- ·Summarisation side-channels through inference
- ·Prompts and answers aren't audited per-user
- ·One AI surface bypasses years of access design
Same question. Different numbers. Every time.
Sales says revenue was 4.2M. Finance says 3.9M. Ops says 4.4M. The AI invents a fourth number from a join nobody validated. The metric definitions live in five spreadsheets — and the AI reads none of them.
- ·No canonical metric layer the AI is bound to
- ·Glossary lives in tribal knowledge and Slack
- ·Different prompts, different math, different result
- ·No way to prove the same question gets the same answer
Each one looks like an AI problem. None of them is. Underneath, they're a grounding problem, a governance problem, and a semantics problem. Jubi treats them as what they are.
Three surfaces. One control plane.
Studio is what people use. Guardian is what enforces every request, native or third-party. Atlas is what grounds the answers.
Chat assistant, dashboard widget, Context Studio. The surfaces people actually use.
Every AI request, gated. Identity, policy, grounding, output validation, audit. End to end.
Canonical metrics, glossary, entity model, permission semantics. The grounding layer.
What people actually use.
Three surfaces, one platform. A business user, a Metabase user, and an analyst all see Studio in three forms.
Every AI request, gated.
Native or third-party, every call routes through Guardian. It checks identity, enforces policy against the user's role, verifies grounding against Atlas, and validates the output before it reaches the user. Every step is logged.
Your enterprise has many AI surfaces, not just ours. Third-party copilots, vendor chatbots, internal agents, one-off integrations. Guardian doesn't care which one — every request hits the same gates.
Each request is checked against the user's identity (from your IdP), the policy bound to their role, and the data they're allowed to reach. Output is validated before delivery. The full trace is logged and replayable: who asked what, what data was touched, what answer was returned.
The result: AI on your data that procurement can sign off on, that audit can reconstruct, and that you can shut off in one place if anything goes wrong.
One perimeter. Two postures.
The AI in your enterprise isn't only what you build. Most of it is what your employees already pay for — copilots, chatbots, coding assistants. Guardian covers all of it, Atlas grounds all of it, on a single control plane.
Bring your own AI
The third-party AI your employees already use: ChatGPT, Copilot, Gemini, vendor-embedded assistants. Guardian sits on the routes that touch your data and tools.
- Identity bound to every call
- Tool-call inspection on every retrieval
- Data egress logged at the gate
- Atlas reachable as a tool
- Connection-level audit across vendors
- Conversation log sits with the vendor
AI you build on Jubi
Agents your teams build on the Jubi platform, running against your data, inside your perimeter. Guardian owns the full request path.
- Full session replay — prompt, response, tool, code
- Inbound + outbound prompt & response scanning
- Atlas-enforced grounding — AI cannot skip
- Outbound network calls denied by default
- Tenant-scoped storage
- SIEM export for security tooling
The AI doesn't invent your numbers. It reads from Atlas.
Most enterprise AI hallucinates because it has nothing to ground against. Atlas is your business written down for the AI to read: canonical metrics, glossary, entity relationships, permission rules. If Atlas can't ground an answer, the AI says so instead of inventing one.
Canonical metrics
One definition of revenue. Not eleven. Verified formulas live in Atlas; the AI uses them, not its best guess.
Glossary & entities
The AI knows what churn means in your business, and that customer, account, and buyer may or may not be the same thing.
Permission semantics
Atlas defines who can see what at the field level. Guardian enforces it on every request, so the AI cannot return what the user isn't allowed to see, whether through retrieval, summary, or inference.
finance.gross_margin_quarterly metric defined in Atlas." — a sourced answer the analyst can verify.None of these works alone.
It's tempting to pick one. Most teams try. The failure mode of each pair tells you why all three are needed.
Governed but ungrounded. The AI is gated, audited, permissioned, and still inventing numbers. Procurement is happy. Finance is not.
Grounded but ungoverned. Answers are correct, but there's no audit, no policy, no isolation. Security blocks rollout in week three.
Safe and grounded, but no surface anyone uses. A control plane for an AI nobody is actually allowed to build.
We slot in. We don't replace.
Jubi sits next to your BI tool, on top of your warehouse, and behind your identity provider. No rip-and-replace. No new database. No new login.
30 minutes. Your data. We'll show what's actually possible.
A short walkthrough on your stack, not a generic deck. We come prepared, you tell us what you wish you could ask of your data, and we show whether Jubi answers it.
- 01Discovery (15 min). What you have. What you've already tried. What good would look like.
- 02Walkthrough (15 min). Live demo on a slice of your data, or on a representative sample if you'd rather we not touch yours yet.
- 03If it makes sense. A scoped 30-day POC with a single workspace. No procurement gymnastics.
Email us with a few words about your stack and what you'd like to ask of your data. We respond within one business day.