Agents now produce huge volumes of code.

42% of new code is now AI-generated. Who's checking it?

Modern codebases have cross-module data flows, API contracts, and architectural invariants that no language model can reason about reliably. Additional LLM reviews share the same potentials for error as the generator.

Archway is a formal verification layer built for this gap. We compile code into a mathematically compact intermediate representation that captures structure without context-window constraints. The result is a verification layer that is provable, not probabilistic.

Bounded changes

AI agents produce localized, bounded diffs — not arbitrary rewrites. Combined with LLM capability to inject domain knowledge, this makes superpowered static analysis tractable for the first time on production-scale code.

Encodable invariants

Codebases have structural invariants — API contracts, data ownership rules, module boundaries — that can be encoded once and checked continuously in CI.

Tools for humans and agents

Deterministic, mathematically derived diagrams give humans instant clarity on code structure. MCP services inject efficient context so coding agents understand both the parts and the whole of the repo they're working in.