Accelerate document review and contract analytics with industry-leading NLP and machine learning.
eBrevia, a Donnelley Financial Solutions (DFIN) company, represents the pinnacle of enterprise-grade contract analytics. Leveraging advanced Natural Language Processing (NLP) and Machine Learning (ML) developed at Columbia University, eBrevia automates the extraction of data from unstructured legal documents with unprecedented accuracy. By 2026, the platform has solidified its position in the market by integrating generative AI capabilities alongside its deterministic ML models, allowing for both precise data extraction and conversational document querying. The architecture is designed for high-stakes environments such as M&A due diligence, LIBOR transition remediation, and global regulatory compliance audits. Unlike standard LLM wrappers, eBrevia utilizes a hybrid approach that combines supervised learning for specific legal concepts with unsupervised learning for pattern recognition across massive datasets. Its integration with DFIN's Venue virtual data room (VDR) provides a seamless end-to-end workflow for corporate transactions, enabling legal teams to reduce review time by 30-90% while significantly mitigating human error in risk assessment.
eBrevia, a Donnelley Financial Solutions (DFIN) company, represents the pinnacle of enterprise-grade contract analytics.
Explore all tools that specialize in contract extraction. This domain focus ensures eBrevia delivers optimized results for this specific requirement.
Proprietary interface allowing non-technical users to train the engine on new concepts by simply highlighting 10-20 examples.
Native processing of documents in over 25 languages using cross-lingual embeddings.
Advanced spatial-aware OCR that reconstructs complex financial tables from scanned PDFs into structured data.
Automated PII and sensitive data identification with bulk redaction capabilities.
Semantic versioning that tracks changes across document iterations even when formatting changes.
Deep integration with the Venue VDR for real-time document analysis during transactions.
Algorithmic weighting of extracted clauses to provide an aggregate risk score per contract.
Contact DFIN sales for enterprise provisioning and tenant setup.
Define administrative roles and security permissions for the internal legal team.
Establish API connection between eBrevia and existing CLM or VDR systems.
Configure 'Project Templates' including the specific fields and clauses to be tracked.
Perform initial bulk upload of historical documents for OCR and indexing.
Utilize the 'User-Trainable Module' to tag unique custom clauses not in the standard library.
Validate system accuracy through a sampled quality control (QC) review process.
Deploy the trained model across the full document repository.
Generate data visualization dashboards for executive risk reporting.
Schedule automated recurring syncs for new document ingestions.
All Set
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Verified feedback from other users.
"Users praise the high accuracy of the out-of-the-box models and the ease of training custom concepts. Some find the enterprise setup process lengthy."
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