Nace AI launches Drex for Search for agent document retrieval
The gains come from cutting agent steps and input tokens by more than half, which lowers API costs on retrieval-heavy workloads rather than just raising accuracy a few points. Teams building agents over enterprise document stores can plug it into Claude Code, Codex or Hermes Agent as a tool. The OfficeQA benchmark result offers a direct comparison point for evaluating retrieval layers before committing to one.
Nace AI launched Drex for Search, a tool that lets agents retrieve answers from cloud-stored files by pinpointing the exact pages they need. The tool searches folder, then file, then page, returning the answer with a quote and page number. It connects to AWS S3, Azure and DigitalOcean, reading scanned PDFs, spreadsheets, email and audio. Coding agents such as Claude Code, Codex and Hermes Agent can use it as a tool, with Nace reporting 62% fewer steps and 56% fewer input tokens per question. Across 529 queries from six professional work benchmarks including Databricks' OfficeQA, agents using it scored 67.1% correct, up from 63.1%.
Nace AI launched Drex for Search, a tool that lets agents retrieve answers from files stored in the cloud by giving them the exact pages they need.
When given a question, Drex for Search first finds the likely folder, then the file, then the page, and returns the answer, the quote, and the page number where it found the info.
> Drex Search is able to connect to a user’s AWS S3, Azure, and DigitalOcean, with the ability to read scanned PDFs, spreadsheets, email, and audio.
> Coding agents such as Claude Code, Codex, and Hermes Agent can use it as a tool, with Nace reporting 62% fewer steps and 56% fewer input tokens per question.
> Across 529 queries from six professional work benchmarks, including Databricks’ OfficeQA, agents using it answered 67.1% correctly, up from 63.1%.
