Introduction

Fuze is runtime safety middleware for AI agents. Wrap any framework, LangGraph, CrewAI, Google ADK, raw OpenAI/Anthropic SDK, to add loop detection, budget enforcement, side-effect tracking, and EU AI Act-compliant audit trails.

What Fuze does

Fuze is not a framework. It's a middleware layer that wraps your existing agent tool calls:

  • Loop detection: 5-layer detection catches ping-pong patterns, semantic stalls, and repetitive tool calls
  • Budget enforcement: hard token, cost, and time ceilings per run with kill switches
  • Side-effect tracking: knows which tool calls changed the real world, with compensation functions for rollback
  • Audit trails: full replayable trace of every agent decision, Art. 12 compliant
  • Smart recovery: retry with modified prompt, rollback to checkpoint, fork to alternate path, or escalate to human
  • MCP Proxy: wrap any MCP server with zero code changes

How it works

Wrap any tool function with guard(), or group multiple steps into a run with createRun(). Fuze handles the rest.

import { createRun } from 'fuze-ai'

async function search(query: string) {
  return await vectorDb.search(query)
}

const run = createRun('my-agent', { maxCostPerRun: 5.00, maxIterations: 50 })
const guardedSearch = run.guard(search)

const results = await guardedSearch('quarterly revenue')

That's it. Every guarded function and every run has loop detection, budget tracking, and audit logging built in.

Deployment modes

ModeDashboardInfrastructure
StandaloneNoNone, just npm install
DaemonREST API at :7821One background process
Cloudapp.fuze-ai.techFUZE_API_KEY env var

Next steps