SigmaForge
Agent 01

DataForgeStatistics you can defend

Thirty-two analyses, from basic statistics and Pareto to ANOVA, regression, capability and control charts. Twenty-eight of the thirty-two are computed by a deterministic engine; the model only writes the explanation.

Book a demoSee the screen

The shape of what DataForge hands back, drawn live.

In the product

What DataForge looks like when you open it

This is the screen itself, captured from the running product on a demo company. Nothing in it was drawn for the website.

Opens at /dataforge once you are signed in.

  • A chart
  • The numbers behind it
  • A written interpretation
  • A saved deliverable
sigmaforge.ai/dataforge
DataForge yield chain for a server mainboard burn-in process: first-pass yield by step, rolled throughput yield of 89.48%, and the burn-in cycle flagged as 55% of the total loss.
Product screen, demo data

Works at the track stage

Something small in, a result you keep

Everything it returns can be saved into the project it belongs to, beside the rest of the work.

What it takes in

  • Pasted values
  • Excel or CSV
  • Screenshot of a table
  • Project measurements

What you get back

  • A chart
  • The numbers behind it
  • A written interpretation
  • A saved deliverable

More of the screen

DataForge, a step further in

  • sigmaforge.ai/dataforge
    The DataForge analysis library: every analysis as a card with a preview of its chart, its DMAIC phase and its belt level, filterable by phase and belt.
    Product screen, demo data

    The DataForge analysis library: every analysis as a card with a preview of its chart, its DMAIC phase and its belt level, filterable by phase and belt.

  • sigmaforge.ai/dataforge
    A saved DataForge yield chain inside an enterprise project: the cascading yield chart, rolled throughput yield, normalized yield, steps and total loss, and the biggest single loss.
    Product screen, demo data

    A saved DataForge yield chain inside an enterprise project: the cascading yield chart, rolled throughput yield, normalized yield, steps and total loss, and the biggest single loss.

All thirteen

The other 12

Each one does one job, and every one has a screen you open.

DataForge on your work

See DataForge on one of your own processes

Thirty minutes, one of your processes, and whichever agents the work calls for. You leave with what they produced.

Book a demoAll thirteen agents