Logic

Logic is a spec-driven agent platform that turns plain-English descriptions into fully managed AI agents with built-in testing, versioning, observability, and model routing. You define what the agent should do using a natural language spec, and Logic handles the how: inferring schemas, orchestrating calls across multiple LLM providers (OpenAI, Anthropic, Google, Perplexity), and exposing the agent as a strictly typed REST API, a web UI, an MCP server, or a batch processor. This eliminates the weeks of wiring up prompts, retries, eval harnesses, and logging normally required before seeing production traffic. The platform is designed for engineering teams building production AI workflows—especially those who need reliability, compliance (HIPAA, SOC 2 Type II), and the ability to iterate without redeploying. Non-technical stakeholders can propose spec changes via approval workflows, while engineers get immutable versions, one-click rollbacks, and CI/CD integration. Each agent ships with auto-generated test suites (synthetic + manual + production replay), automatic regression detection, and field-level failure analysis. What makes Logic different is its abstraction: rather than managing prompts, model configurations, and infrastructure separately, you write a single spec that defines behavior, inputs, and outputs. Logic then manages model routing (cost/latency optimization), execution caching, fallback logic, and multimodal inputs (text, PDFs, images, audio). It also provides a library of starter templates (PII Redactor, Resume Screener, Invoice Extractor, etc.) that you can fork and customize. Logic is positioned as an alternative to stitching together tools like Braintrust, PromptLayer, and custom frontends. It targets teams that want to ship agents faster without sacrificing observability, testing, or compliance. Pricing is based on token usage rather than seats, with a free tier for prototyping and paid plans starting at $49/month for production use.