AI-native - Continuous Planning Platform

Can AI-native ingest code repositories to understand my architecture when generating execution plans?

Yes. AI-native maps your codebase as part of its Context Lake and uses code graph querying to understand architecture constraints. When it generates sprint plans, it considers these dependencies automatically so the tasks it creates account for your actual system structure.

What happens to customer interview transcripts once I upload them to the Context Lake?

AI-native stores transcripts in its unified Context Lake alongside your code, documentation, and tool state. You can then semantic search across them and AI-native will draw on the customer evidence when generating plans. The platform does not publish specifics about data residency or retention, so check their security documentation if your interviews contain sensitive customer information.

Does AI-native replace my existing sprint planning tool or integrate alongside it?

AI-native is built to integrate with existing tools rather than replace them entirely. It handles the upstream work of turning research and code context into sprint-ready execution plans with stories, estimates, and owners. You would then likely move those generated plans into your existing project management system.

Can I use AI-native for free or is there a paid tier?

AI-native operates on a free pricing model. You can run ethnographic research, build a Context Lake from your code and documentation, and generate dependency-aware execution plans without paying.