Products/Automation tools, AI Workflow Automation/Logic

Logic

Build and operate fleets of agents

Automation tools, AI Workflow AutomationFounded 2025Structured spec-driven agent definitionFully managed agents with evals, observability, and versioningMCP, REST, web UI, and dedicated email address accessWell-typed schemas and synthetic test generationRead 130+ document formatsFill out PDF formsSemantic knowledge library searchSend and receive emailResearch capabilityImage generation and annotationHTTP API callingModel routing across OpenAI, Anthropic, Google, and open-source modelsFallback and cost/latency tuningDeep integrations with Linear, Notion, and MCP endpoints

Our Take

Logic is the platform for teams who want AI agents in production without spending weeks reinventing the eval harness and observability wheel every single time. What makes them different is the structured spec approach — you define what the agent should do, they handle the messy parts like versioning, testing, and cost tuning — and their IFBench score speaks for itself, an 83.3% that beat the baseline Gemini model by six whole points. They're already powering four million automated tasks across 250-plus companies with the SOC 2 and HIPAA badges that enterprise buyers actually care about, and honestly, the dedicated email address access thing is a small detail that might actually matter for use cases like user onboarding where bots need to feel like regular correspondence. This is the move if you've already burned out on wiring up LangChain chains by hand and want something built for the long haul.

An AI agent platform where users write a structured spec describing what the agent should do, and Logic provides a fully managed agent with evals, observability, and versioning built in. Agents can be called via MCP, REST, web UI, or dedicated email address.

Problem It Solves
Building AI agents requires weeks of wiring up frameworks, prompts, retries, and eval harnesses before seeing production. The difficult parts include evals, RAG, observability, prompt refinement, model selection, fallback, cost and latency tuning, system integrations, and giving agents tools to interact with external systems.
Target Customer
Development teams building AI agents for production use, including teams at Routable, Paid.ai, Neuranimus, Garmentory, and DroneSense
Use Cases
Content moderation, Document parsing, Data extraction, Medical coding, User onboarding
Free Tier
Free tier available
Differentiator
Scored 83.3% on Allen AI's IFBench (one of the hardest public tests for precise instruction following) - a six-point gain above the same base model (Gemini 3.1 Pro) when called directly
Why Now
250+ organizations have automated over 4M agentic tasks with Logic, and AI agent technology has reached a maturity level suitable for production deployment
Traction
Customers Mentioned: Routable, Paid.ai, Neuranimus, Garmentory, DroneSense · Notable Metrics: 250+ organizations have automated over 4M agentic tasks; 855 followers; 283 points (Day Rank #3); SOC 2 Type II and HIPAA certified

Key Facts

Category
Automation tools, AI Workflow Automation
Founded
2025
Pricing
Paid plans that scale with usage
Discovered via
product-hunt

The people behind Logic

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Azzam Aijazi

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B

Ben Bradley

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Jess Garms

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Joe Lambert

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Mark Golazeski

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Roman Garms

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S

Steve Krenzel

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