Illustration of a processing approach that can be adapted to your organisation and existing tools.
Contracts are essential legal documents that commit the organisation over the long term. Their manual review is time-consuming and prone to interpretation errors.
With portfolios spanning hundreds of contracts in varied formats, legal departments struggle to maintain a reliable overview. Automating contract analysis addresses this need by providing systematic synthesis of commitments and obligations.
Organisations manage contracts of diverse natures: commercial agreements, partnership deals, employment contracts, software licences. Each contract has its own structure, drafted by a different lawyer or legal department, with varied phrasing for similar clauses.
Manual analysis reaches its limits when volume exceeds a few dozen documents. Review times lengthen, some contracts are neglected, and important clauses may go unnoticed. Obtaining a coherent portfolio-wide view without a dedicated tool becomes nearly impossible.
Large language models (LLMs) offer a unique ability to understand the legal meaning of clauses, going far beyond keyword-based search. Unlike rule-based approaches using regular expressions, AI can interpret equivalent formulations and adapt to diverse writing styles.
This approach also allows learning new clause types without complex reconfiguration, simply by providing representative examples. Combined with classification and extraction techniques, it delivers comprehensive document processing from end to end.
The system analyses each contract in several stages. First, the document is converted into machine-readable text via OCR if needed. A language model then identifies the contract structure and locates key sections.
Results are structured as enriched metadata and can be fed into existing tools (DMS, ERP, CRM) via APIs. Human review can be configured for ambiguous cases or critical decisions.
AI-powered contract analysis applies to numerous real-world situations:
AI-based contract analysis requires a rigorous setup phase. The clauses to identify and risk criteria must be defined with the legal department. Result quality depends on source document quality: poor scans or handwritten contracts may reduce extraction reliability.
Organisations deploying an AI contract analysis solution observe several significant advantages:
Several technical building blocks can be combined depending on project objectives:
Q: Can the system analyse contracts in different languages? R: Yes, depending on the models used, analysis can be configured to process contracts drafted in multiple languages. The relevant languages are defined during the project analysis phase based on actual organisational needs.
Q: How are the clauses to be searched defined? R: Clauses and points of attention are defined with the legal department during the design phase. Analysis can cover standard clauses (termination, confidentiality, liability) or clauses specific to the organisation's activity.
Q: Can the system track contract deadlines? R: Yes, expiry, renewal, and termination dates can be extracted and integrated into a tracking system with alerts. The deadlines to monitor are defined according to organisational needs.
Q: What level of reliability can be expected? R: Reliability is assessed on a representative sample before deployment. Cases where analysis is uncertain can be flagged for human review. Analysis criteria can be adjusted to improve result relevance.
To explore complementary approaches, see: - Document classification — for organising and categorising contracts by type - Data extraction — for collecting structured information from contractual documents - Document search — for quickly finding specific clauses or contracts - Knowledge base — for capitalising and sharing contract analyses across the organisation
Every company has its own processes, constraints and tools. The examples presented on this site serve to illustrate what can be envisioned in different contexts.
