Who should use the Analyze contract data workflow?
Teams or solo builders working on finance & legal tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Finance & Legal
Extract key terms, obligations, and risks from contracts using AI-powered contract analysis, then validate and refine findings with legal contract review tools.
Deliverable outcome
Contract data is archived with ongoing monitoring, ensuring no missed obligations or risks.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
Contract data is archived with ongoing monitoring, ensuring no missed obligations or risks.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use Indico Data to all contracts are digitized, readable, and ready for ai analysis. Then, you pass the output to StatsBomb to a structured dataset of key terms and obligations extracted from all contracts. Then, you pass the output to Harvey to a prioritized list of risks across the contract portfolio, ready for legal review. Then, you pass the output to ContractPodAi to all extracted data is human-validated, with corrections and contextual annotations applied. Then, you pass the output to Latitude to stakeholders receive clear, actionable reports summarizing contract obligations and risks. Finally, Avokaado is used to contract data is archived with ongoing monitoring, ensuring no missed obligations or risks.
Upload and preprocess contract documents
All contracts are digitized, readable, and ready for AI analysis.
Extract key terms and obligations using AI
A structured dataset of key terms and obligations extracted from all contracts.
Identify and categorize risks
A prioritized list of risks across the contract portfolio, ready for legal review.
Validate and refine with legal review tools
All extracted data is human-validated, with corrections and contextual annotations applied.
Generate compliance and obligation reports
Stakeholders receive clear, actionable reports summarizing contract obligations and risks.
Archive and monitor for ongoing changes
Contract data is archived with ongoing monitoring, ensuring no missed obligations or risks.
Collect all contract files (PDF, DOCX, scanned images) into a single repository. Use OCR if needed to convert scanned documents into machine-readable text, then normalize formatting (e.g., remove headers/footers, standardize line breaks) to ensure consistent parsing.
Why Indico Data: Indico Data provides document classification and data extraction, which covers OCR-based preprocessing and text extraction for contract documents.
Leverage a contract-specific AI model (e.g., GPT-4 with legal fine-tuning, or a dedicated tool like Kira Systems) to identify and extract critical clauses: parties, effective dates, payment terms, termination conditions, confidentiality, indemnification, and performance obligations. Run the model on each preprocessed document and store results in a structured table.
Why StatsBomb: Harvey specializes in contract analysis and clause extraction, directly matching the need for extracting key terms and obligations from contracts.
Use the AI model to scan extracted clauses for risk indicators such as ambiguous language, unbalanced indemnity, auto-renewal without notice, or missing termination for convenience. Categorize each risk by severity (high/medium/low) and type (financial, legal, operational). Generate a risk summary report.
Why Harvey: Harvey offers contract analysis and clause extraction with legal and regulatory analysis, ideal for identifying and categorizing risks in contracts.
Import the extracted terms and risk flags into a collaborative legal review platform (e.g., Ironclad, ContractPodAi). Assign each contract to a legal professional for validation. The reviewer corrects mis-extractions, adds context, and approves or modifies risk ratings. Use redlining and annotation features to document changes.
Why ContractPodAi: ContractPodAi offers AI-powered redlining and obligation management, directly supporting legal review and refinement of contracts.
From the validated dataset, create actionable reports: a compliance checklist (e.g., GDPR, SOX), an obligation calendar (key dates like renewals, deliverables), and a risk heat map. Use reporting tools (e.g., Power BI, Tableau) to visualize trends across the portfolio. Export as PDF or share via dashboard link.
Why Latitude: Latitude offers embedded dashboard generation and automated data reporting, directly meeting the need for compliance and obligation report generation.
Store the final validated contract data in a centralized repository (e.g., SharePoint, CLM database) with version history. Set up automated alerts for upcoming obligations (e.g., renewal dates, payment deadlines) using calendar integration or workflow triggers. Periodically re-run AI extraction on amended contracts.
Why Avokaado: Avokaado provides automated contract drafting and collaborative redlining, functioning as a CLM platform for archiving and monitoring contract changes.
§ Before you start
Teams or solo builders working on finance & legal tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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