Kena's web index cuts agent search output tokens by 50%
Token-level scoring over its own index means agents fetch only the passages that matter, which lowers API costs for teams running frequent web searches. Builders wiring up agents through MCP or API can swap in KeenableAI as a search backend and immediately halve the tokens their pipeline pays for. Compared with generic search APIs that return whole snippets, this targets long-document retrieval where most waste happens.
