dormakaba

dormakaba's legal team of 9 qualified lawyers (7.8 FTE) plus 3 Contract Managers handled over 10,000 contracts per year across products and markets on all continents. Contract types ranged from simple sales agreements to complex SaaS deals, creating pressure to scale review capacity without linearly growing headcount. Capturing lawyers' implicit review standards into structured playbooks previously took weeks to months of manual Excel work, team alignments, and requirement qualification.

dormakaba implemented Agentic Legal AI via Legartis, centered on automated Contract Playbook creation and outsourced contract review to the business. An AI-driven dialogue captured company context, jurisdictions, risks, and requirements; agents then generated playbooks with definitions, mandatory/optional categorization, risk classification, and validation test sets. The system self-validates instruction interpretation using F-scores on sample cases before scaling review.

Review of a 100-page contract dropped from 1.5 hours to 30 minutes, with lawyers focusing on critical clauses while the system flagged and corrected deviations from corporate standards. Automated playbook creation compressed work that once took weeks or months into hours. Contract review could be globally outsourced to business units, with junior colleagues handling complex contracts under playbook support while Legal focused on strategic matters.

• • Playbook quality and active internal ownership matter more than the tool alone—trial-and-error and cultural change are expected during adoption.
• • Agentic contract review scales best when standards are explicit, validated (e.g., F-score checks), and maintained across contract types and jurisdictions.
• • Start with manageable use cases and measure time, quality, and scalability rather than relying on aggressive FTE-reduction forecasts.