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Sigma Computing

Turn your critical spreadsheets into apps

Use AI to build apps on live warehouse data where teams enter numbers, approve changes, and trigger the next step, under IT’s rules.

  • Writes back to the warehouse

    People work in a familiar grid, and each edit lands in your warehouse as a row.

  • Apps that act on your data

    One button updates a record in your CRM, posts to Slack, or calls your own API.

  • Governed from day one

    Apps inherit your warehouse permissions, with nothing new to host or secure.

Demand planScenariosAccuracySupply
North AmericaMaya ReyesDemand plannerMR

Rolling 12 months · 3 actual + 9 forecast · K cases

Demand plan, Jul '26 to Jun '27

ScenarioHoliday multipackApprovals (1)Submit for approval

Forecast by category

Edit forecast months in your scenario. Quarters sum their months.

Actual, read-onlyForecast, editableLocked
ActualsForecast · Holiday multipack
CategoryJulAugSepQ3 '26OctNovDecQ4 '26JanFebMarQ1 '27AprMayJunQ2 '2712 mo
Sparkling water4524684211,3414023884151,2053523613981,1114264554891,3705,027
Cold brew2142211826172081961885921761811975542102222366682,431
Kombucha1361311283951241181213631151191273611331381424131,532
Electrolyte mix9810487289766461201667284222951081173201,032
Total9009248182,6428107667852,3617097338062,2488649239842,77110,022

Scenarios

Change is vs the baseline, Oct to Jun

ScenarioCategoryChangeStatus
Holiday multipackSparkling water0Draft
Shelf resetKombucha−18KPending approval
Baseline OctAll categories–Baseline

Q3 forecast accuracy

Actual vs the forecast locked Jun 30, K cases

CategoryActualForecastVariance
Sparkling water1,3411,322+1.4%
Cold brew617634−2.7%
Kombucha395391+1.0%
Electrolyte mix289301−4.0%
Total2,6422,648−0.2%

Demand Planning Agent

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I compare scenarios and explain forecast misses with this plan's actuals, shipments, promos and DC inventory.

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One governed process

Get the process out of the shared spreadsheet

Planning, commissions, and operations still run on spreadsheets and one-off apps nobody governs. AI Apps put that work on the warehouse.

TodayWith Sigma
Plans rebuilt by hand in shared spreadsheetsEdits written back as warehouse rows
Numbers that change with whose copy you openOne governed set of numbers for all teams
Custom apps one analyst keeps runningApps built by the team that owns the process
Approvals buried in email threadsActions that start the next step from the app

Everything an app needs to run the business

Build the app, run it on live warehouse data, capture the numbers people enter, and act on them, all in one place.

No backlog

The team that owns the process builds the app

Business teams build apps in a spreadsheet interface they know, adding Input Tables, controls, and buttons with no engineering project. Sigma Assistant builds and edits it on request.

  • Formulas and a grid business teams already use
  • Sigma Assistant builds and edits the app from a description
  • App Templates for common workflows

Always current

Apps run on live warehouse data with nothing to host

Apps read and write the tables in your warehouse, so two apps on the same table show the same row the moment it changes. There are no extracts to refresh and no app servers to run.

  • Queries run live on Databricks, Snowflake, and other warehouses
  • No extracts, copies, or separate app hosting
  • The access rules you set carry into each app

No manual tagging

AI Columns sort the requests your app collects

Point an AI Column at a free-text field to tag each row with the category, theme, or summary you describe. Charts, filters, and KPIs use it once it fills in. AI Columns are in beta.

  • Categories you define in a plain-language prompt
  • Works on reviews, tickets, notes, and form entries
  • Output as text or structured JSON fields

Fully traceable

Edits become rows in your warehouse

Input Tables give people a spreadsheet grid to enter budgets, change requests, and commentary. Sigma writes each change to your warehouse with a record of who changed what.

  • A familiar grid for the people who own the numbers
  • Edits saved straight to your warehouse tables
  • A record of who changed what

One-click handoffs

A button or an agent starts the next step

Actions update the CRM record, notify the owner in Slack, or call your API from an approved row. Sigma Agents work the same rows and ask for approval in chat before changing data.

  • Update Salesforce and other systems
  • Notify owners in Slack or email, or call your API
  • Agents ask for approval before they change data

How teams get there

From shared spreadsheet to governed app

Teams keep the process people already know and move it onto the warehouse, one step at a time.

See the Excel migration skill
  1. 1

    Start from the spreadsheet you have

    Bring the sheet or open an App Template, and point it at your warehouse tables.

    Q4 budget (7) final.xlsx
  2. 2

    Move data entry into Input Tables

    People keep a familiar grid, and their edits land in the warehouse with their names attached.

    DepartmentBudgetMarketing$420KOperations$310KIT$275K+1 row
  3. 3

    Add the actions that come next

    A button on the approved row updates your CRM, notifies the owner, or calls your API.

    Operations Q4 budgetBudget $310KApprovedPost to ERP Budget posted
  4. Let agents watch it

    Agents flag the rows that need a person and handle the routine work within your rules.

    Budget monitor3 departments over planOwners notified in Slack

Apps inherit the rules IT already set

Apps use the same Sigma permissions and warehouse policies as your workbooks, so nothing ships that IT hasn’t already governed.

Visit the Trust Center
  • Writeback on your terms

    Edits write to the warehouse schema your admins choose, under the permissions they already manage.

  • Per-user OAuth

    Connect with OAuth so queries run with each person’s own warehouse role.

  • Row- and column-level security

    Reads and writes both inherit your table policies.

  • Audit trail

    Audit logs record user activity, AI conversations, and input table edits, so you can see who changed what.

  • Your data stays put

    Sigma queries your warehouse in place and never copies the data out.

  • Certified

    SOC 1, SOC 2, SOC 3, HIPAA, GDPR, CCPA, and ISO 27001.

  • “We are building our entire FP&A platform using Sigma, including financial reporting, financial forecasting, budgeting, business & operation KPIs, and customized business processes.”
    Financial AnalystSoftware · Gartner Peer Insights (opens in a new tab)
  • “…its write-back capabilities enable users to build interactive data applications rather than just dashboards.”
    Director of Data and AnalyticsHealthcare and Biotech · Gartner Peer Insights (opens in a new tab)
  • “Our team is able to quickly deliver data-centric apps to support our business stakeholders. We have been able to build apps to facilitate complex reporting, data quality, data transformation, and data curation.”
    Data AnalystFinance (non-banking) · Gartner Peer Insights (opens in a new tab)
  • “We like that it’s not just a BI platform, it’s more of a workflow platform.”
    Andrew DennisDirector of Data · Mid-Market · G2 (opens in a new tab)
  • “Sigma is the first BI tool I have used that offers a true write-back feature, enabling seamless data integration within the analytics layer. This capability has greatly improved team efficiency and reduced data pipeline complexity.”
    Data and Analytics ManagerManufacturing · Gartner Peer Insights (opens in a new tab)
  • “Sigma allows me to set up an AI agent to answer questions about my company’s incentive plan.”
    JamesEnterprise · G2 (opens in a new tab)
  • “Reports are now live, actions can be taken immediately, and collaborating with colleagues is faster and more accurate than it has ever been.”
    Alex BurcumSr. Data Analyst · Small Business · G2 (opens in a new tab)
  • “I love the ability to interact with and create metrics with our data without making core changes to the governed and centralized data warehouse.”

Related resources

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AI Apps FAQ

  • What is an AI App?

    An AI App is an application built in Sigma on live warehouse data. People enter and edit data in Input Tables, actions start the next step in other systems, and Sigma Agents can watch the data and act on it.

  • How is an AI App different from a dashboard?

    A dashboard shows the numbers. An app lets people change them: enter a forecast, approve an adjustment, or update a record, with edits written back to the warehouse.

  • Where does the data go when someone types into an app?

    Into your warehouse. Input Tables write each change to a schema your admins choose, so the edits sit next to the rest of your data instead of in a separate copy.

Bring the spreadsheet your team runs on

We’ll show you the app version, running on your data.