Background: pain points of the digital office
In modern office scenarios, unstructured data such as financial reports, scanned contracts, meeting recordings, etc. account for more than 80%. Traditional manual entry is not only time-consuming (an average of 15-30 minutes per document), but also prone to fatigue leading to errors.
Cloudsquid's complete solution
- Step 1: Batch Upload Mixed Files Drag and drop to upload PDF, JPG, MP3, etc. on the web side, and the system automatically recognizes the content type
- Step 2: Natural Language Instructions Enter the requirements in the extraction options (e.g. "Extract all contract signatories and amounts"), support for mixed Chinese and English descriptions.
- Step 3: Intelligent Parsing Verification The AI will be at the time of processing:
- Automatic alignment of related data in multi-page PDFs
- Recognize handwriting in pictures (accuracy 92%)
- Extracting key fields after converting audio to text
- advanced skill: The use of "|" to separate multiple conditions (e.g. "Withdrawal amount | greater than €1000") improves accuracy 20%
Typical Efficiency Comparison
Tests showed that when processing 100 mixed documents:
Manual: 25 hours | Cloudsquid: 8 minutes (accelerated 187 times)
This answer comes from the articleCloudsquid: upload documents and describe requirements for intelligent extraction of structured dataThe
May not be reproduced without permission:AI productivity tools " How to solve the efficiency problem of manually extracting data from multi-format files?
