Business users can build an automated document processing pipeline by following these steps:
- Private deploymentContact technical support to get a Docker image and deploy it to a local server (8-core CPU/16GB RAM required) to ensure data isolation.
- system integration: Using the REST API (
api.fast360.xyz/ocr/batch) Docking OA / ERP system, support concurrent processing of 100 + documents - Intelligent Routing: Automatically assign models according to document types: Contracts → MinerU, Bills → OCRFlux, Manuals → Marker
- Results-based management: Registered business accounts can create a proprietary document library, supporting the storage of JSON-structured data by date/item classification
- Exception handling: Set Webhook to receive notification of processing failures and automatic retry mechanism to ensure process continuity.
This answer comes from the articleAI Fast Station: document parsing tool for comparing OCR models in one clickThe
May not be reproduced without permission:AI productivity tools " A complete solution for realizing enterprise-class OCR document batch processing
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