Built for the obvious decisions

One call instead of five models

Today teams wire up five models: an intent classifier, a sentiment model, a moderation model, an extractor and a router that decides when to call the big reasoning model. Simo is all five in one call.

The headline three

• Agent supervision: done-ness, next action with its arguments, and risk, one call per step.
• Act, think or ask: act at 0.95, call the reasoning model at 0.60, ask a human below that.
• Ticket and inbox triage: route, urgency, the customer’s temperature and the order ID in one request.

The rest

• Visual QA assertions: assert on pixels in milliseconds, with no brittle selectors.
• Moderation and policy screening: thousands of items an hour with auditable probabilities.
• LLM judging at production scale: “is this answer supported by the context?” on every response.
• Visual inspection: read the label and judge the condition from one photo.
• Document and form reading: typed, schema-valid fields straight from the page.
• Video event detection: frames in, calibrated event probabilities out.

Where Simo fits, and where it does not

Simo supervises the controller; it is not the controller. Use it where a decision takes milliseconds, not where motors do. Robot motor control and game input are not what it is for.