Framer Introduces AI Component Library That Learns from Team Repositories

Design · 5 min read

The library uses a code-aware model to scan design and code repositories, identify repeated patterns (cards, navbars, modal flows), and offer vetted components that match a team's conventions. Each suggested component includes an accessibility audit, recommended props, and a test harness for integration testing.

Framer emphasizes privacy: scanning and model inference can run within a company's cloud account, and generated artifacts link back to source locations so engineers can accept or update provenance. The feature pairs with a 'component lint' tool that flags inconsistent spacing, color token mismatches, and semantic markup problems.

Product teams report that the library reduces duplicated work and accelerates componentization in cross-functional squads. Some engineering teams caution that auto-generated components still require code review and performance profiling before production use.