Contract Review Orchestrator
Coordinates contract analysis from extraction through redlining and version tracking
Extract key terms, flag risky clauses, suggest redlines, track versions
Reviewing third-party contracts is a meticulous, time-intensive process where missing a single unfavorable clause can expose the organization to significant liability or unfavorable economic terms. This agentic workflow uses natural language processing to extract key terms (pricing, duration, liability caps, indemnification), flags non-standard or risky clauses by comparing against internal playbooks, and suggests specific redline changes to mitigate risk. By tracking negotiation versions and alerting counsel to unfavorable terms early in the process, this approach accelerates contract review while improving risk identification. Enterprises deploying agentic contract review see 50% faster review cycles and catch risky terms earlier in negotiations, achieving 8-12x ROI through both time savings and risk avoidance. Industries with complex supplier relationships, high-stakes agreements, or frequent contract negotiations—such as financial services, insurance, technology, healthcare, energy and utilities, and real estate—benefit most from this intelligent review assistance, as it allows legal teams to focus strategic judgment on the most critical terms rather than manual clause extraction.
Agent Architecture
An orchestrator coordinates extraction of key contract terms, risk analysis, and redlining suggestions to accelerate legal review.
Contract Review Orchestrator
Coordinates contract analysis from extraction through redlining and version tracking
Term Extractor
Extracts key terms from contracts using NLP
Risk Analyzer
Flags risky or non-standard clauses
Redline Suggester
Suggests specific redline changes
Extract key terms from contract (price, duration, liability)
Flag non-standard or risky clauses
Compare to playbook and risk appetite
Suggest redline changes
Track negotiation versions
Alert to unfavorable terms
Click any KPI to view detailed measurement guidance, formulas, and typical ranges.
Capture all agent interactions (prompts, outputs, data sources accessed) in a central, searchable system
Central inventory of all agents with metadata: owner, purpose, data sources, risk level, users
Automatically detect and mask PII in agent interactions, especially before logging or sending to external APIs
Define how long to retain agent logs, prompts, and outputs. Balance audit needs with privacy obligations.
Regularly test agents for vulnerabilities (jailbreaks, prompt injection, data exfiltration attempts)
These controls help ensure secure, compliant, and auditable AI operations. High-priority controls are critical for production deployment.
AI generating false or fabricated information presented as fact
AI using outdated data that no longer reflects current reality
Inability to verify or cite the original sources of AI-generated information
Non-compliance with data privacy regulations like GDPR and CCPA
Accidental disclosure of confidential business or customer information
Lack of proper consent for recording, storing, or processing user interactions
Unintentional exposure of sensitive data through model training or outputs
Malicious manipulation of AI behavior through crafted input prompts
These risks should be mitigated through proper governance controls and operational procedures.
Track regulatory changes, assess impact, update policies, notify stakeholders
Receive request, check templates, generate draft, route for review
Search for keywords, categorize documents, flag privileged material, prepare production
Explore assistive AI tools that Legal teams use to augment these agentic workflows.
Applying AI to legal workflows? Olakai delivers the compliance monitoring and risk governance that legal teams require.
Schedule a Demo