Logic

Build and operate fleets of agents

Logic Introduction

Logic is a spec-driven platform that lets you define AI agents using structured specifications, then deploys them as fully managed, production-ready APIs with built-in evals, observability, and intelligent model routing. It eliminates the weeks of manual wiring and infrastructure setup typically required to ship a real AI agent, enabling teams to build and operate fleets of agents in minutes.

Key Features

Structured spec-based agent definition with typed inputs/outputs
Automated evals, observability, and logging out of the box
Intelligent model routing across OpenAI, Anthropic, Google, and Perplexity with automatic failover
Auto-generated API docs, shareable web UI, and MCP server integration
Batch processing for running agents against entire CSV datasets

Use Cases

Developers quickly building and deploying custom AI agents for customer support, data processing, or automation
Product teams creating internal tools with natural language interfaces and managed APIs
Enterprises needing to orchestrate multiple AI agents with consistent monitoring and fallback strategies
AI researchers prototyping and testing agent behaviors with built-in evaluation harnesses

Why Startups Use It

Startups need to move fast, and Logic lets you launch AI agents in minutes instead of weeks. By abstracting away model routing, observability, and evaluation, Logic reduces infrastructure overhead and allows small teams to focus on core product logic. Its built-in best practices and scalable API also mean startups can iterate quickly without worrying about production readiness.

Alternative Options

LangChain, AutoGPT, CrewAI, Vellum, Agno

Frequently Asked Questions

How quickly can I deploy a logic agent?

Under 60 seconds. Write a structured spec describing what the agent should do, and Logic generates a typed, tested, versioned API endpoint immediately.

What infrastructure does Logic manage?

Logic handles schema validation, typed APIs, model routing with retry logic, automated testing and versioning, and full execution logging—so you don't need to build any of that yourself.

How does model routing work?

Logic automatically routes each request to the optimal model across OpenAI, Anthropic, Google, and Perplexity based on task complexity, cost, and latency requirements. Failover is automatic.

Can I integrate Logic agents with other tools?

Yes, agents expose a REST API, come with auto-generated API docs, and support MCP for native integration with tools like Claude, Cursor, and ChatGPT. You can also process batch jobs via CSV.