Every AI memory system chops your knowledge into fixed-size pieces, so ideas get split, context gets lost and answers go wrong. ARR draws its boundaries dynamically around meaning, and makes any AI you connect it to dramatically smarter about what you know.
Most retrieval systems split every document every few hundred tokens, wherever the count lands. Switch between the two modes to see the difference.
ARR moves reasoning into the retrieval step itself, so the AI receives complete, connected ideas instead of random fragments.
Boundaries are placed where one idea ends and the next begins, not every 512 tokens. Each piece is a complete thought, whatever its length, so the AI needs fewer calls to get the full picture. Our target is 20% fewer retrieval calls.
Related ideas are connected across documents, like decisions, causes, people and dates, so retrieval can follow a chain of thought.
Connect ARR to the AI you already use. It gets whole context instead of fragments, and its answers improve without changing the model.
Notes, research, ideas and reading turned into a memory your AI can really think with.
Meetings, decisions and documents connected, so anyone can ask what was decided and why.
Company knowledge that answers accurately instead of guessing from fragments.
Plug ARR into your own AI apps and fix retrieval quality at the source.
We're opening ARR to a small group of early users first. Join the list and we'll contact you when your place is ready.