Overview
Allibee Legal OCR is a high-performance optical character recognition API specifically engineered for accurate text extraction from legal documents, public records, and contracts. Powered by GPU-accelerated deep learning models, Allibee Legal OCR ensures exceptional accuracy across diverse document qualities, automatically correcting skewed or distorted text regardless of orientation. It supports a comprehensive range of file formats including multi-page PDFs, TIFF, and modern image formats like AVIF and HEIC, making it compatible with any source-from scanned archives to mobile captures. Designed for enterprise-scale capability, the service efficiently processes large files up to 100MB with concurrent page-level parallelism. Advanced features include configurable confidence scoring, automatic reprocessing of low-confidence regions, and flexible region exclusion to protect sensitive information. Allibee Legal OCR returns structured JSON responses containing precise bounding box coordinates and rich metadata, enabling seamless downstream data processing. Allibee Legal OCR integrates natively with AWS cloud infrastructure, supporting both RESTful API endpoints and AWS Batch Transform for serverless, high-volume processing. Whether you are digitizing vast legal archives, automating form data entry, or processing government records, Allibee Legal OCR delivers the production-grade reliability, error handling, and performance required for mission-critical document automation workflows.
Highlights
- Legal-Specific Accuracy: Specialized deep learning models extract high-precision text from contracts and government records, automatically correcting skewed or low-quality scans.
- High-Performance Processing: GPU-accelerated engine handles large multi-page files (up to 100MB) and diverse formats (PDF, TIFF, HEIC) with fast concurrent processing.
- Seamless AWS Integration: Native support for RESTful API and AWS Batch Transform. Returns structured JSON with bounding boxes and confidence scores for reliable automation.
Details
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Pricing
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g5.2xlarge Inference (Batch) Recommended | Model inference on the ml.g5.2xlarge instance type, batch mode | $0.99 |
ml.g6.2xlarge Inference (Real-Time) Recommended | Model inference on the ml.g6.2xlarge instance type, real-time mode | $0.99 |
ml.g5.xlarge Inference (Batch) | Model inference on the ml.g5.xlarge instance type, batch mode | $0.99 |
ml.g4dn.xlarge Inference (Batch) | Model inference on the ml.g4dn.xlarge instance type, batch mode | $0.99 |
ml.g6e.4xlarge Inference (Real-Time) | Model inference on the ml.g6e.4xlarge instance type, real-time mode | $0.99 |
ml.g6.4xlarge Inference (Real-Time) | Model inference on the ml.g6.4xlarge instance type, real-time mode | $0.99 |
ml.g6e.8xlarge Inference (Real-Time) | Model inference on the ml.g6e.8xlarge instance type, real-time mode | $0.99 |
ml.g5.xlarge Inference (Real-Time) | Model inference on the ml.g5.xlarge instance type, real-time mode | $0.99 |
ml.g5.2xlarge Inference (Real-Time) | Model inference on the ml.g5.2xlarge instance type, real-time mode | $0.99 |
ml.g4dn.xlarge Inference (Real-Time) | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $0.99 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Version release notes
This release introduces Allibee Legal OCR, a specialized high-precision engine designed for accurate text extraction from contracts and government records. It features GPU-accelerated processing for large multi-page documents, support for diverse formats including HEIC and AVIF, and native integration with AWS Batch Transform for scalable automation.
Additional details
Inputs
- Summary
The model accepts document files via RESTful API requests or AWS Batch Transform. Supported inputs include standard image formats (JPEG, PNG, TIFF, WebP, AVIF, HEIC) and multi-page PDFs up to 100MB. For API invocations, the input content must be provided as binary data in the request body.
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