What is Contract Analytics Software?
Contract analytics software is a technology solution that uses artificial intelligence and machine learning to automatically extract, analyze, and report on data within contracts. Concord’s analytics software transforms unstructured contract text into structured, actionable insights that help organizations manage risk, improve compliance, and optimize contract performance.
Contract Term Extractor
Paste your contract text below to extract key terms and information
Case Study: Custom Properties Unlock Strategic Contract Data at LeoVegas
500+ hrssaved annually
2 weeks → 1 dayproject turnaround
Instantdata extraction
Key Benefits:
- • Custom property tagging
- • Instant filtering & reporting
- • Proactive renewal management
LeoVegas struggled to extract key data from complex contracts with multiple addenda and revisions. Legal spent 10 hours weekly searching for information, delaying critical decisions.
How Concord helped:
- • Concord’s custom properties tag contracts by jurisdiction
- • Filter and sort hundreds of contracts instantly
- • Generate reports in minutes - not weeks
“The custom properties functionality, that’s where Concord really helps us save time. Projects that used to take two weeks to do manually can now be done in a single afternoon.”— Michael Cuschieri, Head of Legal
Case Study: AI-Powered Contracts Accelerate Sales at PAAY
AIautomated data extraction
Fastersales cycles
100%contract visibility
Key Benefits:
- • Automated PDF data extraction
- • Hubspot integration
- • Built-in redlining
PAAY's manual contracting processes created sales bottlenecks. Their legacy system couldn't scale with growth, delaying deal closures.
How Concord helped:
- • Concord's AI extracts data from any document format
- • Direct Hubspot sync eliminates manual entry
- • Mobile redlining enables deals anywhere
"There's no other contract platform that delivers this much value at this price point. Concord has just been great for us."— Jamie Garfield, VP Sales
From legal document to strategic assets, through contract analytics
Contract ownership is evolving beyond the legal department. Concord’s 2024 survey of finance and operations leaders revealed that 100% of respondents noted that contract management is becoming a cross-functional imperative. CFOs, finance heads, operations managers, and procurement specialists are all taking greater ownership of the contract process.
As Nikos Anthopoulos, Efficiency Manager at Navarino, explains: “I’m under the office of the CEO. My role is to help processes and software run faster.” This statement captures the strategic importance that organizations now place on contract efficiency.
See Concord's contract analytics software in action.
Automated data extraction and analysis
Advanced contract analytics software leverages natural language processing (NLP) and machine learning to automatically extract key information from agreements, including:
Parties and signatories
Key dates (effective dates, expiration dates, renewal deadlines)
Financial terms and obligations
Service level agreements (SLAs)
Risk factors and compliance requirements
Michael Bearman, Chief Legal & Safety Officer at Vecna Robotics, highlights the transformative impact of this automation: "I used to have to spend lots of time on this, but now I just hit 'create document' because the AI does a great job automatically. Before we'd make errors like missing key dates or transposing numbers, which caused problems down the line. Now, with Concord, that information is automatically captured and validated, so we can trust its accuracy."
Centralized contract repository with advanced search capabilities
The lack of real-time visibility into contract data is a major pain point for organizations. In Concord's 2024 survey, 100% of finance and operations leaders highlighted this issue as a significant challenge.
As Gaia Olcese, Procurement Manager at Satispay, notes: "Better visibility would be amazing. We have more than 12,000 contracts, and their data is not sorted." This inability to quickly find and analyze contract data hinders proactive management, creates inefficiencies, and exposes organizations to unnecessary financial risk.
Modern contract analytics platforms address this through:
Centralized storage for all agreements
Advanced search functionality that locates specific clauses and provisions
Customizable tags and metadata for efficient organization
Optical character recognition (OCR) to make even scanned documents searchable
Automated categorization of contracts by type, department, or risk level
Proactive renewal management
Effective renewal management represents a significant opportunity for cost savings. Research indicates that 88% of organizations struggle with managing contract renewals effectively, often missing opportunities to renegotiate terms or accidentally allowing unfavorable agreements to auto-renew.
David Morgan, CFO at Loop Returns, articulates this challenge succinctly: "We've passed an auto renewal cut off date, and now we're locked in." This highlights the financial repercussions of delayed decision-making.
Advanced contract analytics platforms address this through:
Automated alerts for upcoming renewal dates
Renewal workflows that assign tasks to responsible stakeholders
Historical spending analysis to inform renewal negotiations
Vendor performance tracking to support data-driven renewal decisions
The role of AI in modern contract analytics
Current AI capabilities and limitations
Artificial intelligence is dramatically reshaping contract repository software, offering unprecedented efficiency and insights. A comprehensive market analysis found that 88% of finance and operations leaders recognize AI's transformative potential, while acknowledging the need for careful implementation and human oversight.
AI's current capabilities in contract analysis include:
Automated data extraction: Identifying and classifying key contract elements
Clause recognition: Spotting standard and non-standard clauses
Risk identification: Flagging potentially problematic language or terms
Pattern recognition: Identifying trends across contract portfolios
Anomaly detection: Highlighting unusual provisions that deviate from standards
However, AI in contract analytics also has important limitations:
As Pepe Carr, General Counsel at Sand Technologies, observes: "If your learning model can raise their hand and say, 'I don't know what this is, please take a look,' then you are off to reduce legal headcount." This highlights the value of "human-in-the-loop" systems, where AI assists legal professionals by flagging potential issues for review rather than making final decisions autonomously.
Tammy Carroll, Contract and Strategy Manager at OneCare Vermont, reinforces this perspective: "You still need a human." This reflects the understanding that AI should be seen as a tool to augment, not replace, human judgment.
Future directions in AI-powered contract analytics
As natural language processing and machine learning continue to advance, we can expect to see AI contract analytics expand in several directions:
Predictive analytics: Using historical data to forecast potential contract outcomes and suggest improvements
Conversational interfaces: Allowing users to query contract data using natural language
Automated benchmarking: Comparing contract terms against industry standards and suggesting optimizations
Integration with negotiation processes: Real-time guidance during contract negotiations
Contextual understanding: Better comprehension of industry-specific terminology and requirements
Integration: The key to creating a “single source of truth
The challenge of data silos
The concept of a “single source of truth” for contract data is a powerful ideal. However, Concord’s survey revealed that 75% of finance and operations leaders acknowledge that achieving this ideal is more complex than it seems. Data silos, where contract information is scattered across ERPs, CRMs, specialized tools, and even email inboxes, are the primary obstacle.
David Morgan, CFO at Loop Returns, describes how his billing team often has to “crack open the PDF” because not all contract information syncs with their billing system. This reliance on unstructured data highlights the inefficiency and potential for errors inherent in manual reconciliation.
The integration imperative
Modern legal contract management software platforms address this challenge through robust integration capabilities. Research indicates that 75% of organizations consider seamless integrations between contract lifecycle management systems and other core business applications to be essential.
Christopher Tufts, FP&A Manager at Iterable, emphasizes this point: “An integrated CLM is important so we can serve all our principal audiences from the same system.”
Effective integrations should include:
Two-way data synchronization: Ensuring data consistency across systems
Automated triggers: Initiating actions in other systems based on contract events
Native integrations: Pre-built connections to common business applications
APIs and webhooks: Enabling custom integrations for specialized needs
Implementation best practices: A phased approach
Successfully implementing contract analytics requires a strategic, phased approach that balances quick wins with long-term transformation. Based on insights from finance and operations leaders across various industries, here is a recommended implementation roadmap:
Phase 1: Quick wins (within 3 months)
Conduct a contract inventory audit: Identify where contracts are stored, what data is captured, and where inconsistencies exist
Implement standardized naming conventions and tagging: Improve searchability and lay the groundwork for future automation
Start tracking key contract metrics: Measure active contracts, total contract value, and average cycle time to establish a baseline
Phase 2: Short-term priorities (within 6-12 months)
Evaluate and select a CLM solution: Prioritize data accuracy, robust reporting capabilities, and integration potential
Implement automated alerts for key contract dates: Begin proactive management of renewals and deadlines
Explore AI-powered solutions: Start automating data entry and basic contract analysis
Establish clear guidelines for AI usage: Maintain human review and validation of AI-generated insights
Phase 3: Long-term investments (12+ months)
Foster a culture of contract awareness: Establish clear roles and responsibilities across departments
Explore advanced analytics capabilities: Implement risk scoring, anomaly detection, and predictive analytics
Track and communicate ROI: Measure contract cycle time reduction, cost savings, and compliance improvements
Continuously refine and optimize: Evolve processes based on data and user feedback
Choosing the right contract analytics solution
Key evaluation criteriaWhen evaluating contract analytics solutions, organizations should consider:Data extraction accuracy: The system’s ability to correctly identify and extract key informationIntegration capabilities: Native connections to existing business systemsUser experience: Intuitive interfaces for legal and non-legal usersAI capabilities: Current functionality and development roadmapSecurity and compliance: Data protection measures and regulatory adherenceCustomization options: Ability to adapt to specific business needsImplementation support: Training, onboarding, and ongoing assistanceTotal cost of ownership: Subscription fees, implementation costs, and ROI potential
The Concord advantage
Concord’s Agreement Intelligence platform stands out as the best contract lifecycle management software, through its:AI-powered data extraction that automatically identifies key terms, dates, and obligationsIntuitive interface that requires minimal training for both legal and non-legal usersRobust integration capabilities with popular CRM, ERP, and financial systemsComprehensive workflow tools that streamline contract processesAdvanced analytics that provide actionable insights into contract portfoliosAs Jamie Garfield, VP of Sales at PAAY, observes: “Concord has just been great for us. We adore the AI features. There’s no other contract platform that delivers this much value at this price point. Period.”
Contract Analytics Solution Comparison (May 2025)
Need to know
Frequently Asked Questions
Conclusion: The future of contract intelligence
The evolution from basic contract management to sophisticated analytics represents a fundamental shift in how organizations view and leverage their agreements. This transformation is driven by the growing recognition that contracts are not merely legal documents but strategic assets rich with data that can inform business decisions and drive financial performance.As we look to the future, the integration of increasingly sophisticated AI capabilities will continue to expand the possibilities of contract analytics. From predictive insights to automated benchmarking to natural language interfaces, these advancements will further enhance the strategic value of contract data.Organizations that embrace this digital contract management transformation—viewing their contracts as sources of business intelligence rather than administrative overhead—will gain significant advantages in operational efficiency, risk management, and strategic decision-making.The time to begin this journey is now. By starting with a clear assessment of current contract processes, implementing quick wins to demonstrate value, and developing a strategic roadmap for more advanced capabilities, organizations can transform their approach to contracts and unlock the full potential of their agreement data.
About Concord: Concord empowers growing businesses to make smarter operational decisions by unlocking actionable insights from all their contracts using Agreement Intelligence. Trusted by over 1,500 companies and 1 million users worldwide, Concord enables people to swiftly sign agreements and easily access crucial business data. www.concord.app
