Spec-driven authoring
Write a plain-English spec that defines behavior, inputs, and outputs. Logic interprets the spec and builds the agent from it, which the site says can work with natural language specs or SOPs.
Logic
Logic is a spec-driven agent platform that turns plain-English specs into production agents and typed APIs, with built-in validation, versioning, deployment, and observability.
Overview
Logic is a spec-driven agent platform that turns plain-English specifications into production agents and APIs. It is designed for teams that want to define agent behavior in a spec and let the platform handle the infrastructure around testing, routing, versioning, deployment, and logging.
The site positions Logic as a way to ship production AI without assembling separate tools for prompt engineering, evals, orchestration, routing, or observability. Agents can be tested, versioned, and exposed as typed REST APIs, with additional delivery options such as a web app and MCP server.
Core capabilities
Built-in validation
Generate and run tests from the spec, including synthetic test generation, inline test cases, regression detection, and side-by-side failure review. The platform also supports CI/CD integration through its API.
Version control and approvals
Publish immutable versions, compare changes, pin integrations to versions, and roll back with one click. Approval workflows let non-technical editors propose changes while engineers review them before release.
Deployment surfaces
Expose each agent as a strictly typed REST API, plus a web app, MCP server, and CSV batch workflow. Logic also auto-generates docs and integration guides from the spec.
Model routing and caching
Route requests across OpenAI, Anthropic, Google, and Perplexity with automatic model selection and failover. The platform also includes execution caching for deterministic workloads.
Execution observability
Log each execution with full context, including inputs, outputs, model reasoning, and latency. The Observe capability is meant to make failures easier to trace across agent versions.
Common use cases
Build agents from specs
Teams can describe the desired agent behavior in plain English and let Logic infer schemas, orchestration logic, and a production-ready implementation.
Validate changes before release
Product, operations, or compliance workflows can use the platform to test outputs against expected results before changes go live, reducing regressions after edits.
Ship agents into existing workflows
Organizations can publish agents as typed APIs for internal tools, batch CSV processing, or a shareable web interface without building a separate app layer.
Manage reviewed agent updates
Teams that need review gates can use approval workflows and immutable versions so non-technical editors can propose changes while engineers control release.
Route work across model providers
Organizations working across different model providers can route requests automatically and fall back when a provider errors or goes down.
Pros and Cons
Pros
- Combines spec writing, testing, versioning, deployment, and observability in one platform.
- Turns agent definitions into typed APIs and other delivery surfaces without separate frontend or documentation tooling.
- Supports automatic model routing and failover across multiple major providers.
- Includes approval workflows and immutable versions, which can fit teams with review requirements.
- Offers a free tier and a paid path for production use, with unlimited users on every plan.
Cons
- The source materials do not provide a full list of external integrations beyond model providers and MCP-related capabilities.
- Some feature details are broad and do not spell out exact limits, supported frameworks, or implementation requirements.
FAQ
What is Logic used for?
Logic is a spec-driven agent platform for turning plain-English specifications into production agents and REST APIs. The platform handles orchestration, testing, versioning, deployment, and execution logging so teams can ship and update agents without building that infrastructure themselves.
How do teams access agents built in Logic?
Logic exposes agents as strictly typed REST APIs, and the features page also says agents can be available as a web app and MCP server. It generates API documentation and integration guides from the spec, plus a shareable web UI with input forms.
Does Logic have a free tier or paid plans?
The pricing page offers a Free plan, a Pro plan at $49/month, a Scale plan at $299/month, and an Enterprise option that requires contacting sales. The plans are token-based and include unlimited users on every plan, with higher tiers adding more tokens, storage, retention, and support.
What are the main platform capabilities?
The features page says Logic includes a built-in test harness, immutable versioning, one-click rollback, intelligent model routing, execution logging, and approval workflows for new agent versions. The pricing page also lists capabilities such as MCP client support, batch processing, knowledge library, and multimodal inputs.
Which external integrations are supported?
The source materials do not list a full integration catalog or every supported external system. They do state that Logic supports OpenAI, Anthropic, Google, and Perplexity for model routing, plus MCP and agent tools such as email and HTTP.
Quick Facts
- Category
- Developer Tool
- Product type
- Spec-driven agent platform
- Primary workflow
- Write a spec, test it, version it, and deploy it as an API
- Website
- logic.inc
- Pricing model
- Free tier plus paid token-based plans
- Deployment outputs
- REST API, web app, MCP server
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