The spreadsheet your team already trusts
Sigma works like the spreadsheet operators live in, except every number underneath is the same governed source of truth. Familiar on top, solid underneath.
On governed dataThe instruments Sigma
The analytics your operators actually open
Sigma is the analytics surface that works like the spreadsheet your team already trusts, on governed data, with AI agents that answer in plain English. We turn it into analytics operators use, because adoption beats elegance every time.
The hard truth
A dashboard nobody opens is not analytics
Most analytics stop at a dashboard that looks impressive in the demo and goes unopened by week three. The team exports everything back to the spreadsheet it trusts.
Adoption beats elegance. The surface has to feel like where operators already work, with governed data underneath, or the investment never gets used.
Analytics your operators trust beats analytics that only impress.— Hitesh Mahajan, Founder, Aidapt
Sound familiar?
You bought the tool. The team went back to the spreadsheet
- You bought a BI tool, and the team still exports everything back to a spreadsheet.
- The dashboards look impressive in the demo and go unopened by week three.
- Only the analyst can answer a new question, so every question waits in a queue.
- The numbers in the report and the numbers in the spreadsheet do not match.
- Leadership wants to explore, but the tool only lets them look.
What we build
Familiar on top, governed underneath, AI on the same data
Answers without a queue
Your team asks the next question themselves, drilling and filtering live, without exporting or waiting on the analyst. Curiosity stops being a ticket.
Self-serve, safelyAn AI agent on the same data
Ask the workbook a question and an agent reads the governed model, surfaces the finding, and proposes the next step. The judgement stays yours, the legwork goes.
Plain English, governedWhere it earns its place
Built for operators, opened on Monday
01
Operator analytics
Live, explorable views built for the people running the business, not just the analytics team.
02
Adoption that holds
A surface familiar enough that the team opens it on Monday, so the investment underneath actually gets used.
03
Governed self-serve
Exploration without the chaos: everyone explores, every number traces back to one source of truth.
Intelligence on the surface
Ask the data a question, in plain English
The newest reason operators open Sigma: an AI agent that reads the same governed model the workbook does. It answers the next question, names what changed, and proposes the step after — so exploration is not gated behind the one person who knows SQL.
How it runs
Translated first, then built to be used
The same order every time. The diagnostic decides which decisions the surface serves before a single workbook is built.
01Translate
We map the decisions your operators make, and where the current analytics lose them.
02Build
The workbooks, views and AI agents built on governed data, in the shape your team already thinks in.
03Embed
Trained role by role in real work, so the surface is opened daily, not admired once.
04Evolve
Views extend as the questions change. The team keeps exploring without us.
Fit
Transparency saves everyone’s time
A good fit when
- Your team trusts spreadsheets more than the BI tool you already bought.
- An operator wants to explore the numbers, not just look at a dashboard.
- You have governed data underneath, or are building it.
- Adoption matters more to you than a beautiful demo nobody opens.
Probably not when
- You want dashboards shipped with no view on the decisions they serve.
- There is no governed data underneath and no plan to build it.
- You expect the tool alone to make a team trust the numbers.
- The decision belongs to a tooling committee, not an operator.
Common questions
Asked by operators, answered plainly
How is Sigma different from the BI tool we already have?
Sigma works like the spreadsheet your team already trusts, on governed data. Adoption beats elegance: the team opens it because it feels familiar, and every number underneath is the same source of truth. We choose the instrument per engagement, and the diagnostic will say so if your context calls for a different surface.
What does the AI inside Sigma actually do?
It reads the same governed model the workbook does, so you can ask a question in plain English and get an answer traced to real data, not a guess. It surfaces the finding and proposes the next step, while the decision stays with the operator. We build the agents into the views people already use, so nobody has to remember to use the AI.
Do we need a data warehouse first?
Sigma is the surface, not the foundation. It reads governed data, so it works best on a modelled source of truth. If that foundation is not there yet, the diagnostic will sequence it.
Will people actually use it?
That is the whole point of choosing it. The surface is familiar enough that operators open it without training, and we embed it role by role in real work so adoption holds after launch.
Who owns it after?
You do. Your workbooks, your governed data, your team running it without us. We build the capability, then the surface keeps earning.
Do we start with Sigma?
No. Every engagement enters through a diagnostic, not a tool. We read how your work moves first, then decide where the surface earns its place.
Start here
Start with a translation, not a tool
Every engagement enters through one doorway: a diagnostic, not a tool. Begin with a free Impact Analysis, or go straight to the Diagnostic when you are ready.