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Jessie A Ellis
Feb 12, 2026 05:53

Legal AI startup Harvey unveils high-throughput file ingestion system capable of processing hundreds of thousands of documents from enterprise DMS platforms.

Harvey AI has rolled out a new file ingestion architecture designed to handle hundreds of thousands of legal documents from enterprise document management systems, addressing a critical bottleneck in how law firms feed institutional knowledge into AI tools. The system targets a fundamental problem: large law firms sit on millions of documents containing deal structures, motion templates, and negotiation playbooks scattered across platforms like iManage, SharePoint, and Google Drive. Getting that context into AI systems—and keeping it fresh—has been a manual nightmare. What Changed Harvey’s previous approach relied on synchronous file processing with manual uploads. Users had to select individual files rather than folders, and documents went stale whenever someone updated the source. The new system introduces two core features: one-click folder uploads that preserve entire hierarchies with metadata, and continuous one-way sync that automatically detects and pulls changes from connected DMS platforms. The technical backbone uses Temporal for workflow orchestration—a choice driven by the unpredictable nature of enterprise file operations. Traffic spikes, external rate limits, and transient failures are constants when crawling millions of documents across distributed systems. The Engineering Tradeoffs Harvey’s team made each API request a separate Temporal activity during folder crawling. This granularity means hitting a rate limit on page 47 of a 200-page folder listing triggers a retry for just that request, preserving progress on the previous 46 pages. File downloads follow the same isolation pattern—one file failing doesn’t tank the batch. Rate limiting turned out to be the hidden complexity. Each integration partner enforces limits differently: by request count, payload size, or both; scoped per-user or per-organization; sometimes…

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Filed under: News - @ February 13, 2026 12:24 am