Legal, procurement, and finance teams spend significant time reading contracts and orders, extracting key fields, tracking clauses, and rekeying data into systems. Long documents, layout variability, scanned annexures, and handwritten notes make manual reviews slow and error prone, raising cost and compliance risk.
AI assisted extraction structures clauses, tables, and metadata, highlights obligations and risks, and surfaces low confidence outputs for quick review. Teams shorten cycle time, improve accuracy against SLA targets, and enable safer decisions without changing upstream document formats.
This total cost of ownership calculator helps you evaluate the true ROI of the category using modern AI powered alternatives over traditional OCR based solutions.
Key Use Cases:
Table and Structured Data Extraction
Detects and extracts tables from invoices and contract annexures with correct row and column mapping for downstream systems.
Handwritten and Scanned Document Recognition
Handles low quality scans and handwritten annotations, signatures, or stamps using image preprocessing and handwriting recognition.
Contract and Payment Term Compliance
Validates due dates, early payment discounts, and penalties against predefined contract or purchase order terms.
Audit Trail Generation
Captures metadata and clause changes over time to create a searchable history for compliance and disputes.
Clause Extraction
Identifies and extracts clauses such as payment terms, termination rights, liability limits, confidentiality, jurisdiction, and force majeure for search and review.
Metadata Extraction
Extracts contract ID, parties, dates, renewal terms, governing law, and signatory details for structured storage.
Obligation Extraction
Identifies obligations of each party for compliance monitoring and operational tracking.
Payment Term Extraction
Extracts payment frequency, amounts, due dates, penalties, and escalation clauses for finance and operations teams.
Non Standard Clause Detection
Compares clauses to templates to flag unusual or risky terms for legal review.
Risk Clause Identification
Detects clauses with financial or legal risk that require elevated scrutiny.
Change of Control Detection
Finds and tracks change of control obligations triggered by mergers, acquisitions, or ownership changes.
Jurisdiction and Governing Law Extraction
Extracts jurisdiction and governing law to support compliance and dispute resolution.
Signature and Party Validation
Verifies signatories and involved parties against internal records or external data.
Multi Language Processing
Uses multilingual NLP to extract and translate clauses, metadata, and obligations across languages.
Contract Amendment Detection
Compares contract versions to detect added, removed, or modified clauses for audit trails.
Start by selecting a typical scenario or adjust the baseline details to reflect your exact needs. The calculator will update automatically.
If your organization relies on legacy OCR for contract data capture, accuracy typically caps at about 80% struggles with handwritten contracts, poor scans, and complex tables, forcing analysts to manually recheck and re-enter data. This results in higher costs and slower processing cycles.
Modern AI that combines OCR with natural language processing and advanced models lifts accuracy to approximately 92% accuracy ±2%, generalizes better across layouts. However generic AI cannot pinpoint which fields are wrong with certainty, so teams still verify low confidence outputs and critical fields to protect legal and financial controls.
Your AI investment isn’t delivering expected savings. This may indicate inefficiencies or incorrect assumptions in your current workflow.
Contact us to identify more optimization opportunities.
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