SchemaGate Output Gate

Validate AI output against business rules before it becomes a real action

Problem

Once an AI agent is wired into real systems, teams fear a single non-compliant output turning into a charge, an email, or a data change. Today they review logs after the fact; there is no generic gate that decides allow/flag/regenerate/block/human-review before the action fires, which is why one builder spent six months on this and still doubted demand.

Solution

A lightweight validation layer: developers declare an output schema and business rules, the agent calls one API before acting, and it returns allow, flag, regenerate, block, or escalate with the reasoning logged. A visual rule editor lets non-engineers adjust thresholds.

Users

Small teams wiring agents into production systems; indie developers and integrators building AI automation

MVP

JSON schema validation; composable rule expressions; a single API with five decision types; decision logs and replay view; SDK wrappers for common agent frameworks

Revenue

Usage-based pricing per validation call with a free tier, then subscription; enterprise tier with self-hosting and rule audit

Why now

Agents are moving from demos to real actions, making output validation urgent, while big platforms only cover their own models, leaving room for a model-agnostic thin layer