Shipping a real AI agent can mean weeks of wiring up prompts, retries, eval harnesses, and logging before you see production. Logic solves that. You write a structured spec that describes what the agent should do, and Logic gives you a fully managed agent, with evals, observability, model routing and more built in, ready to be called from anywhere.
When you build an AI agent, the call to the LLM API is the easy part. The hard parts are evals, RAG, observability, prompt refinement, model selection, fallback, cost and latency tuning, system integrations, and giving the agent tools to do useful work in the rest of the world.
Logic gives you an out-of-the-box answer for all of that, while also improving how reliably your agents follow instructions.
With Logic, you write a simple spec that explains what the agent should do. We give you back a managed agent that can be called via MCP, REST, a web UI, or a dedicated email address. We generate well-typed schemas and synthetic tests, handle versioning, observability, and RAG, and give your agents a "batteries included" tool suite:
Real-World Capabilities: All Logic agents can read 130+ document formats, fill out PDF forms, semantically search your knowledge library, send and receive email, do research, generate and annotate images, and call HTTP APIs.
Smart Model Routing: Route across OpenAI, Anthropic, Google, and hardware-accelerated open-source models, with fallback and cost/latency tuning, so you can improve reliability without being locked into one provider.
Deep Integrations: Easily connect to external tools like Linear, Notion, and any MCP endpoint.
We make your agents smarter.
When Logic's agent harness was measured against Allen AI's IFBench, one of the hardest public tests for precise instruction following, Logic scored 83.3% – higher than any model on the Artificial Analysis leaderboard. This is a six-point gain for the agent harness above the same base model (Gemini 3.1 Pro) when called directly.
So far, 250+ organizations have automated over 4M agentic tasks with Logic. Common use cases include things like content moderation, document parsing, data extraction, medical coding, and user onboarding.
Logic is SOC 2 Type II and HIPAA certified, there's a free tier, and paid plans that scale with usage.
Jess, my co-founder and CTO, and I will be in the comments. We're excited to see what you build with it, and we'd love to hear what else you wish it could do.
Thanks for taking a look.
About Logic on Product Hunt
“Build and operate fleets of agents”
Logic launched on Product Hunt on April 27th, 2026 and earned 283 upvotes and 26 comments, earning #3 Product of the Day. Shipping a real AI agent can mean weeks of wiring up prompts, retries, eval harnesses, and logging before you see production. Logic solves that. You write a structured spec that describes what the agent should do, and Logic gives you a fully managed agent, with evals, observability, model routing and more built in, ready to be called from anywhere.
On the analytics side, Logic competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how Logic performed against the three products that launched closest to it on the same day.
Who hunted Logic?
Logic was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Logic including community comment highlights and product details, visit the product overview.
Ben Lang
Hey Product Hunt. I'm Steve, co-founder of Logic.
When you build an AI agent, the call to the LLM API is the easy part. The hard parts are evals, RAG, observability, prompt refinement, model selection, fallback, cost and latency tuning, system integrations, and giving the agent tools to do useful work in the rest of the world.
Logic gives you an out-of-the-box answer for all of that, while also improving how reliably your agents follow instructions.
With Logic, you write a simple spec that explains what the agent should do. We give you back a managed agent that can be called via MCP, REST, a web UI, or a dedicated email address. We generate well-typed schemas and synthetic tests, handle versioning, observability, and RAG, and give your agents a "batteries included" tool suite:
Real-World Capabilities: All Logic agents can read 130+ document formats, fill out PDF forms, semantically search your knowledge library, send and receive email, do research, generate and annotate images, and call HTTP APIs.
Smart Model Routing: Route across OpenAI, Anthropic, Google, and hardware-accelerated open-source models, with fallback and cost/latency tuning, so you can improve reliability without being locked into one provider.
Deep Integrations: Easily connect to external tools like Linear, Notion, and any MCP endpoint.
We make your agents smarter.
When Logic's agent harness was measured against Allen AI's IFBench, one of the hardest public tests for precise instruction following, Logic scored 83.3% – higher than any model on the Artificial Analysis leaderboard. This is a six-point gain for the agent harness above the same base model (Gemini 3.1 Pro) when called directly.
So far, 250+ organizations have automated over 4M agentic tasks with Logic. Common use cases include things like content moderation, document parsing, data extraction, medical coding, and user onboarding.
Logic is SOC 2 Type II and HIPAA certified, there's a free tier, and paid plans that scale with usage.
Jess, my co-founder and CTO, and I will be in the comments. We're excited to see what you build with it, and we'd love to hear what else you wish it could do.
Thanks for taking a look.