Logic - AI Reasoning Engine

Write specs, ship agents - no code required.

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Updated Jul 2026 · Added Jun 2026

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What is Logic?

Logic is a spec-driven agent platform that lets you write AI agents in plain English and deploy them as production-ready APIs in seconds. Define agent behavior, inputs, and outputs through natural language specs - no frameworks or SDKs required. Built-in testing, versioning, intelligent model routing, and observability ensure your agents are reliable, stable, and debuggable from day one.

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Key Features of Logic

Spec-driven agent design in plain English
Built-in test harness with automatic regression detection
Git-like version control with instant rollback
Strictly typed REST API auto-generation
Auto-generated API docs and web UI
Intelligent model routing across OpenAI, Anthropic, Google, Perplexity
Automatic failover and execution caching
MCP server integration for Claude, Cursor, ChatGPT
Batch processing via CSV
Complete execution logging with full context
Approval workflows for non-technical spec editors
CI/CD integration via API

Who Should Use Logic?

Scan and redact personal data from text with detailed reporting

Evaluate product listings against policies and provide moderation decisions

Analyze contracts to flag risky clauses and extract key terms

Match records across systems with confidence scoring

Extract structured line items from invoices and POs

Personalize onboarding experiences based on signup context

Score and screen resumes against job descriptions

Triage support tickets by priority, sentiment, and category

Logic: Pros & Cons

✓Pros

Eliminates need for separate frameworks, SDKs, and custom code
Inline testing with automatic regression detection catches issues early
Version control with transparent diffs and instant rollback provide stability
Intelligent model routing optimizes cost and latency automatically
Automatic failover ensures reliability
Execution caching provides instant results for deterministic workloads
Complete observability with full execution logging and context
Approval workflows enable non-engineers to update agent logic
MCP server integration allows native use in Claude, Cursor, and ChatGPT
Batch processing simplifies bulk operations

Frequently Asked Questions about Logic

Can I write Logic agents in plain English without learning a framework?

Yes. Logic specs are written entirely in plain English, not code or YAML. You describe what the agent should do, what inputs it accepts, and what outputs it produces, then Logic generates a fully typed REST API and deploys it immediately. No SDKs or frameworks required.

How does Logic's version control work, and can I roll back an agent?

Logic uses Git-like version control, so every spec change creates a new version with transparent diffs. You can roll back to any previous version instantly if something breaks. Combined with built-in regression testing, this means you can iterate on agent behavior without fear.

Does Logic route requests across different AI models automatically?

Yes. Logic includes intelligent model routing that can automatically choose between OpenAI, Anthropic, Google, and Perplexity based on cost and latency. It also handles automatic failover if your primary model is unavailable, and caches results for deterministic tasks so repeated requests return instantly.

Can I use Logic agents inside Claude or Cursor without building custom integrations?

Yes. Logic runs as an MCP server, so you can integrate agents natively into Claude, Cursor, and ChatGPT without writing any glue code. You can also trigger agents via REST API for CI/CD pipelines or batch processing through CSV files.