Machine Learning / Artificial Intelligence / Advanced Rules

Enlighta’s Govern ML, uses advanced Machine Learning, Extraction Rules and AI technologies to enable automation of:

• Contract Extraction, Analysis & Updates
• Invoice Extraction and Validation
• Contract Generation

Govern ML : Contract workbench for Extraction, Analysis and Updates

Govern ML’s Contract workbench for Contract Extraction, Analysis and Updates uses Machine Learning and Extraction rules to:

• Automate the identification of document type based on uploaded contract documents (MSA, SOW, NDA Etc.)
• Auto-generate and link contract hierarchies
• Automate clause identification and clause extraction
• Automate identification of SLAs, Pricing and Obligations

Enlighta Govern ML not only extracts and analyzes the data but also updates and creates the relevant records (performance, compliance & financial) to enable the ongoing governance of the contracts.

Govern ML : Invoice workbench for Extraction & Analysis
Enlighta’s Govern ML, powered by Machine Learning algorithms and Extraction Rules, speeds up the process and improves the accuracy of Supplier Invoice Validations. The data from the supplier invoice is extracted, the quantity and rates are auto identified and compared against the contractual rates and actual quantity. The comparison is done and in case of an issue/ discrepancy, the invoice issue is auto created, enabling issue tracking and escalations.
Govern ML : Contract workbench for Contract Generation
Enlighta’s Govern ML uses advanced technologies to enable faster and accurate generation of contracts that comply with organizations contract standards and contractual policies helping to reduce contract drafting time, save cost and improve compliance.

The system refers to the organization templates for MSAs, SOWs and Amendments to auto generate SOWs and amendments for drafting in word/doc format with relevant clauses and auto populates pricing and SLA tables, enabling organizations to quickly draft contracts that are in compliance with organizations contractual policies.
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