Reductov1.0.3

Finance teams use the extract_data action to pull structured JSON from PDF invoices, receipts, and purchase orders according to a custom JSON Schema. This eliminates manual data entry and feeds clean, validated line items into accounting or ERP systems.

AI engineers parse complex PDFs and documents into structured chunks, blocks, and metadata using parse_document, then embed that content into vector databases. This improves retrieval accuracy for enterprise search, chatbots, and knowledge assistants.

Legal operations teams use split_document to break long agreements into named page sections based on natural-language descriptions. This speeds up contract review, clause extraction, and routing to the correct reviewer or workflow.

Claims teams extract structured fields from medical records, policy documents, and claim forms submitted as PDFs. The extracted data populates adjudication systems, reduces manual review time, and improves turnaround accuracy.

Analysts parse investment research, regulatory filings, and market reports into structured chunks for downstream analysis and summarization. Extracted data can feed dashboards, alerting systems, or LLM-powered research copilots.

Reducto charges based on the number of pages or documents processed through its API actions. Customers pay only for the parsing, extraction, or splitting volume they consume, making it easy to scale up or down.

Reducto offers monthly plans with included processing volumes, higher rate limits, and premium features such as custom schemas or priority parsing. Tiers are designed for individuals, growing teams, and enterprise accounts.

Large organizations purchase custom enterprise agreements that include dedicated support, security reviews, SLA guarantees, and integration assistance. These deals often bundle higher-volume processing and advanced document workflows.