Process Unstructured Data from Documents at Scale

Unstructured documents come in all layouts and formats. From invoices, POs, contracts, to bank statements, claims, and medical records, each document presents a unique extraction challenge. ReportMiner handles all of them.

These extraction methods cover every scenario:

• Template-Based Extraction For documents with a consistent layout, Auto-Generate Layout (AGL) uses AI to detect the document structure and build a reusable extraction template in 5 seconds — automatically applied across all files that share that format. Built-in OCR ensures scanned PDFs and image-based documents are converted to machine-readable text before the template is applied.
• Template-Less Extraction For documents with no consistent format, natural language prompts instruct the AI on what to extract and how to organize the output — no template required. Built-in OCR handles scanned or image-based inputs here too, so unstructured documents are never a barrier.

Both methods support Google OCR, Amazon Textract, PaddleOCR, and Tesseract.

ReportMiner does not require coding, scripting, or any technical configuration. Operations and data teams build and deploy extraction workflows directly.

The visual interface lets users interact with document content to define fields, set rules, and preview results in the same environment:

• Point-and-Click Template Builder define extraction fields by clicking directly on document content — field names, types, and positions are set visually
• Real-Time Data Preview verify extracted data at every step of template creation before exporting — issues are visible before data moves anywhere
• Dynamic Customization Options relevant settings surface based on the part of the template being configured — no unnecessary complexity

Empower your team to work independently without IT dependency.

Extraction errors are easier to fix before data reaches downstream systems. ReportMiner surfaces extracted data in real time as templates are built and adjusted.

Preview capabilities operate at every stage:

• Live Preview Window extracted data updates immediately as fields are defined — what the output will look like is always visible
• Format Verification confirm output structure and data completeness before exporting to any destination

Reduce manual rework and ensure data quality from the start.

Not all documents follow simple structures. ReportMiner includes detailed controls for capturing data from complex layouts such as hierarchical documents, key-value pairs, and tabular data with collection items.

Customization operates at the field level and the model level:

• Hierarchical Extraction define parent-child data structures for documents like order reports and inventory lists — export as JSON, XML, or structured database tables per entity
• Calculated Fields create derived fields using a library of 200+ built-in functions — aggregations, conversions, and calculations run at extraction time
• Automatic Field Verification checks for missing characters and overlapping fields automatically, flagging issues before they affect output

Tailor your extraction to match your exact business requirements.

Extracted data is not automatically clean data. ReportMiner includes validation and transformation capabilities that run as part of the extraction pipeline, before data is delivered.

Data quality is not a separate step. It is built in:

• Data Cleansing remove noise, unwanted characters, punctuation, and whitespace from extracted fields — output is clean before it reaches its destination
• Validation Rules define custom rules to enforce accuracy and consistency — ReportMiner reports error counts, null counts, and warnings per job
• Built-in Transformations handles type conversion, column restructuring, aggregation, and calculation without additional tooling

Deliver clean, reliable data to your downstream systems.

Manual extraction does not scale. ReportMiner automates the full document processing pipeline, from file ingestion through validation and delivery, without manual steps between stages.

Automation runs at the workflow level:

• Job Scheduler set run frequencies or trigger jobs on file drop — workflows execute automatically without user action
• Distributed Execution run jobs on a single server or distribute across multiple servers — processing capacity scales with volume
• Real-Time Job Monitoring track all deployed jobs from a centralized dashboard — set alert emails for errors, completions, and abnormal terminations

Build enterprise-grade automation without complexity.