Logic.inc

Logic.inc is an AI project builder tool that writes a spec in plain English, ship a tested production agent. Logic turns a plain English agent spec into a typed, versioned REST API in under a minute, with built-in testing, automatic model routing across OpenAI, Anthropic, Google and Perplexity, deployment docs and full execution logging.

Logic is a spec-driven platform for building and running AI agents. Instead of wiring together frameworks, SDKs and orchestration code, a team writes a natural language spec that defines what the agent does, what it accepts as input and what it returns. Logic turns that spec into a typed, versioned REST endpoint that can be called from anywhere. The company positions the product around the infrastructure most teams build before their first AI feature ships: schema validation, model routing, retries, testing, versioning and execution logging. In practice the workflow is short. A user picks one of the published templates (contract clause analysis, invoice and PO extraction, PII redaction, resume scoring, ticket triage, listing moderation and others) or writes a custom spec from scratch. Saving the spec produces an API endpoint, auto-generated documentation, an input form and a shareable web UI. Requests are routed automatically across OpenAI, Anthropic, Google and Perplexity, with faster models handling simple work and frontier models reserved for harder reasoning, plus failover if a provider errors out. Every execution is logged with inputs, outputs, reasoning, latency and error detail, so a broken agent can be traced to a specific version. The platform suits two distinct audiences. Engineers get stable API contracts, a test harness that runs expected-output checks on every save, and batch processing over a CSV. Operations, legal and support teams get approval workflows and version pinning, so non-technical editors can adjust decision rules without redeploying code. Published customers include Garmentory, which scaled product moderation from 1,000 to 5,000+ listings per day, and DroneSense, which cut complex purchase order handling from about thirty minutes to two. Alternatives tend to solve one slice of the problem. Prompt management tools, eval frameworks and routing layers each cover a piece, and teams can assemble them into a stack. Logic's argument is consolidation with typed APIs and rollback built in. The tradeoff is dependence on a managed abstraction: model choice is handled for you rather than picked by hand, and the spec-first style is less suited to agents that need fine-grained custom code or unusual tool chains.