A mid-size law firm handling 500+ contracts monthly across M&A and real estate practices was losing its most valuable resource: associate time. Associates were spending 85% of their working hours on manual document review — extracting key terms, flagging non-standard clauses, and cross-referencing compliance requirements across hundreds of pages of contracts.
The problem was especially acute on complex multi-party agreements where the risk of missing a critical clause was highest. Each contract required careful reading, manual extraction of obligations and deadlines, comparison against the firm's standard templates, and documentation of any deviations. A single missed clause could expose the firm's clients to significant liability.
The firm had tried general-purpose AI tools, but they lacked the legal domain knowledge to reliably identify the specific clause types, obligations, and risk patterns that mattered for M&A and real estate work. What they needed was a system trained on their specific practice areas, templates, and risk criteria.
DxLogic built a custom AI document processing pipeline tailored to the firm's M&A and real estate practices. The system reads contracts in any format — PDF, DOCX, and scanned documents — using OCR and natural language processing to extract the full text and structure of each agreement.
The AI then analyzes each contract against the firm's standard templates, extracting key terms and obligations, identifying non-standard clauses, flagging potential risks, and generating a structured summary for partner review. The system was trained on the firm's specific clause library and risk criteria, meaning it identifies the exact issues that matter for their practice areas.
Partners receive a concise summary of each contract highlighting deviations from standard terms, potential risks, key deadlines, and obligations. Associates who previously spent their days reading contracts can now focus on higher-value advisory work — analyzing the issues the AI flags rather than finding them manually. The system was implemented in 3 months from kickoff to full production deployment.
Manual review time dropped by 85%, freeing associates from the most tedious part of their work. Missed clauses and errors were reduced by 95% — the AI consistently catches issues that human reviewers miss under time pressure. The 3-month implementation timeline meant the firm saw ROI within the first quarter. Associates are now spending their time on substantive legal analysis and client advisory work instead of document processing.
“Our associates went from reading contracts all day to actually practicing law.”
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