Extract key dates, parties, financial terms, obligations, and compliance requirements from PDF contracts into organized spreadsheets
Organizations of every size maintain contract portfolios ranging from dozens to thousands of agreements. Vendor contracts, customer agreements, lease agreements, employment contracts, NDAs, service level agreements, and partnership deals accumulate over years of business operations. The vast majority of these contracts exist as PDF files stored in shared drives, document management systems, or email folders. The data inside them — renewal dates, financial commitments, termination notice periods, performance obligations, and compliance requirements — is effectively invisible to anyone who has not read each document individually.
This invisibility creates real business risk. A contract auto-renews because no one tracked the 90-day notice deadline. A vendor continues billing at an old rate because the rate adjustment clause buried on page 14 was never surfaced during a pricing review. An obligation to deliver quarterly reports goes unfulfilled because the commitment was documented in a contract exhibit that the operational team never saw. Insurance certificates lapse because the renewal tracking spreadsheet was maintained manually and the coordinator changed roles. These are not hypothetical scenarios; they represent the daily reality of contract management when contract data exists only inside PDF documents.
Lido converts contract documents to Excel by extracting the critical data points from each agreement into structured spreadsheet columns. Upload your contract PDFs and get a contract register with party names, effective dates, expiration dates, financial terms, renewal conditions, and key obligations organized for sorting, filtering, and tracking. The AI reads each contract independently regardless of format, length, or structure. Start with 50 free pages.
Party identification and roles. Every contract involves at least two parties, and the AI identifies each party's legal name, role in the agreement (buyer, seller, licensor, licensee, landlord, tenant, employer, contractor), and contact information when present. For contracts with multiple parties, guarantors, or named subcontractors, each entity is captured with its role designation. This is more nuanced than it appears, because contracts use varying conventions to introduce parties: "ABC Corp, a Delaware corporation ('Buyer')" or "hereinafter referred to as 'the Vendor'" or simply naming both companies in the opening paragraph without explicit role labels. The AI parses all of these conventions.
Critical dates and deadlines. Contracts contain multiple date fields that drive business actions: effective date, execution date, term start date, initial term expiration, renewal option dates, termination notice deadlines, price adjustment dates, and milestone due dates. The AI extracts all date references and categorizes them by type, producing an Excel row where each date type occupies its own column. For contracts with auto-renewal clauses, the AI calculates the notice deadline based on the specified notice period and the current term expiration, so teams can set reminders at the right time without manually computing these dates.
Financial terms and pricing structures. The financial section of a contract may contain fixed fees, hourly or daily rates, volume-based pricing tiers, minimum commitment amounts, annual escalation percentages, payment schedules, late payment penalties, and performance bonuses. The AI extracts each financial element as a separate field in the Excel output. For rate cards that appear in pricing schedules or exhibits, the full rate table is captured with service descriptions and their corresponding rates, enabling procurement teams to compare contracted rates against market benchmarks or across multiple vendor agreements.
Beyond dates and dollars, contracts contain operational obligations that must be tracked and fulfilled. Service level agreements define uptime targets, response time commitments, and remedies for non-compliance. Scope of work sections describe deliverables, acceptance criteria, and milestone timelines. Compliance clauses specify insurance requirements, certification maintenance, reporting obligations, and audit rights. The AI identifies these obligation types within the contract text and extracts the key parameters: what must be done, by whom, by when, and what happens if the obligation is not met. This transforms a 30-page contract PDF into an actionable row of trackable commitments in a spreadsheet.
Contract extraction differs fundamentally from invoice or receipt extraction because contracts are primarily prose documents rather than structured forms. An invoice has clear field labels and a tabular layout that indicates what each value represents. A contract embeds its critical data within paragraphs of legal text, defined terms, cross-references, and conditional clauses. The AI must understand the meaning of the text, not just its visual position, to extract the relevant data points.
The extraction process begins with document structure analysis. The AI identifies the contract's organizational hierarchy: recitals, defined terms, numbered articles or sections, subsections, schedules, and exhibits. It maps this structure to identify which sections contain which types of information. Financial terms are typically in a pricing or compensation section. Term and termination provisions have their own section. Confidentiality, indemnification, and governing law each occupy distinct portions of the agreement. By understanding this structure, the AI knows where to look for specific data types and can extract them with contextual accuracy.
Within each section, the AI performs semantic extraction rather than keyword matching. It understands that "the initial term shall be twenty-four months commencing on the Effective Date" means the term length is 24 months, even though no field label says "Term Length: 24 months." It recognizes that "either party may terminate this Agreement by providing not less than ninety days' prior written notice" establishes a termination notice period of 90 days. This semantic understanding enables extraction of data that is expressed in natural language rather than formatted as labeled fields.
Real contracts are messy. Amendments modify original terms without restating the entire agreement. Side letters create additional obligations. Master service agreements establish frameworks that are activated by individual statements of work or purchase orders. The AI handles these relationships by extracting data from each document in the contract family and linking related documents through shared reference numbers or party names. When an amendment changes the expiration date from a contract's original terms, the extracted data reflects the amended date, not the superseded one, with a note indicating the amendment source.
Legal teams building contract registers. Legal departments responsible for contract lifecycle management need a centralized register showing every active agreement with its key terms. Converting the contract portfolio to Excel produces this register automatically: party names, agreement types, effective dates, expiration dates, auto-renewal terms, governing law, and financial commitments in a single sortable spreadsheet. This replaces the manual contract abstracting process that paralegals typically perform, which takes 30 to 60 minutes per contract and is the primary bottleneck in building or updating a contract management database.
Procurement teams managing vendor agreements. Procurement teams need visibility into vendor contract terms for renewal planning, rate negotiations, and compliance monitoring. Converting vendor contracts to Excel reveals which agreements are approaching renewal, which vendors have rate escalation clauses triggering this year, and which contracts include minimum commitment amounts that affect purchasing decisions. This structured view enables proactive renewal management rather than reactive scrambling when a vendor flags an upcoming auto-renewal or rate increase.
Finance teams tracking contractual commitments. Financial planning requires visibility into future contractual commitments. Lease obligations, software subscription commitments, service contract minimums, and employment agreement compensation terms all represent future cash outflows that must be budgeted and forecasted. Converting these contracts to Excel produces a commitment schedule that finance teams can aggregate by period, category, and business unit, feeding directly into budget models and financial projections.
Compliance teams monitoring obligation fulfillment. Organizations subject to regulatory requirements, ISO certifications, or contractual compliance obligations need to track whether those obligations are being met. Converting compliance-relevant contracts to Excel creates an obligations tracker where each requirement is listed with its responsible party, due date, and completion status. Insurance certificate expiration dates, annual audit requirements, reporting deadlines, and training obligations become visible and manageable rather than buried in contract documents that no one regularly reviews.
Upload contract PDFs and get a structured Excel spreadsheet with every critical term, date, and obligation extracted
Yes. AI-powered extraction reads contract documents and identifies key dates including effective date, expiration date, renewal date, and notice period deadlines. It also captures financial terms like contract value, payment schedules, rate cards, and fee structures. These fields are mapped to Excel columns, producing a contract register spreadsheet where every agreement's critical dates and terms are visible in a single sortable, filterable view without opening individual contract PDFs.
Contracts typically contain multiple sections covering different aspects of the agreement: scope of work, pricing, payment terms, termination clauses, indemnification, and confidentiality. The AI reads the full document structure, identifies section headings and their content, and extracts the relevant data points from each section. Financial terms from the pricing section, deadlines from the term section, and obligations from the scope section all map to appropriate columns in a single Excel row per contract.
Yes. Upload your contract PDF archive and the AI extracts party names, obligations, deliverable descriptions, milestone dates, and compliance requirements into a structured Excel spreadsheet. This produces an obligations tracker where you can filter by party, sort by deadline, and identify upcoming deliverables or compliance milestones across your entire contract portfolio. The tracker replaces the manual process of reading through each contract to find obligation dates and requirements.
Yes. Many contracts include schedules, exhibits, and appendices that contain critical details like rate cards, service level agreements, scope descriptions, and insurance requirements. The AI processes the entire document including attachments, extracting relevant data from schedules and exhibits alongside the main agreement terms. Rate tables in pricing schedules are captured as structured data, and SLA metrics from service level exhibits are extracted with their target values and measurement criteria.
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