Use cases

Certificate of analysis are received in pdf format from suppliers, so in critical applications the data from these documents is manually re-entered, and for non-critical ones, they are stacked away after visual check. Automated extraction of data from certificates of analysis will reduce manual effort, and create a complete record of data that can be used for quality troubleshooting, improving the spec, etc.

Toxicology test results are received in diverse PDF formats from vendor labs and are manually entered into systems, which is time-consuming and prone to errors. Automated extraction will ensure accuracy and reduce cycle time for safety assessments.

Raw material specs come from multiple vendors in inconsistent formats, making comparison and entry into ERP difficult. Automated extraction will standardize and speed up material qualification and procurement.

Maintenance teams receive product brochures in various PDF formats that contain critical specs and parts info. Extracting this info allows better asset management and quicker reference during repairs.

Supplier vetting documents often come as unstructured forms and attachments. Extracting key data like certifications, experience, and financials helps build a structured supplier database and accelerates vendor qualification.

Supplier quotes come in many formats. Extracting line items, prices, delivery terms, and validity periods enables rapid comparison and faster procurement decisions.

Contracts with smaller vendors are often stored as PDFs or scanned copies without structured metadata. Extracting contract terms, renewal dates, and SLAs enables proactive management and compliance.

Fuel expense invoices and reports from logistics providers are manually reviewed and reconciled, often leading to errors. Automated extraction improves accuracy and speeds up payment processing.

Documents related to freight settlements come in scanned form or emails and require manual data entry for claims and settlements. Automated extraction supports faster claims and reduces disputes.

Instead of just tracking fuel costs, extracting actual consumption data from invoices and reports enables accurate sustainability reporting and carbon footprint analysis.

Competitor product sheets often come as PDFs or brochures. Extracting specs and features allows marketing and product teams to perform competitive analysis.

Prospective customer and start-up data often arrives as unstructured documents or emails. Extracting relevant info supports business development and partner management.

Marketing assets such as brochures and flyers are often stored in unstructured formats. Extracting metadata allows better asset management and version control.

Calibration certificates for lab equipment are typically issued as scanned PDFs by third-party vendors. These need to be manually entered into LIMS or maintenance systems. Automated extraction ensures accurate record-keeping, audit readiness, and easier calibration scheduling.

Import/export documents such as commercial invoices, packing lists, and certificates of origin often arrive in PDF formats. Extracting structured data helps ensure faster customs clearance, reduce compliance risks, and support duty optimization strategies.

Employee or asset insurance claims are submitted using scanned forms or PDFs, requiring manual review and data entry. Automated extraction enables faster processing, supports fraud detection, and improves reporting accuracy.

Internal and external audit reports are typically narrative-style documents that include findings, corrective actions, and risk ratings. A data extraction tool can help standardize this information for trend analysis, risk tracking, and audit closure reporting.

Recruiters often receive resumes in varying formats and manually extract key candidate information. Automating this can help populate ATS databases faster and enable structured candidate profiling for quicker shortlisting.

Feedback forms submitted through email or scanned documents often contain structured information such as ratings, issue types, and contact info. Extracting this data supports better customer service analytics and prioritization.

Patent filings include highly structured information but are available only in dense PDF formats. Automated extraction of claims, assignees, and filing history enables faster IP landscape analysis and competitor tracking.

Utility invoices for electricity, gas, and water are often received as PDFs. Extracting consumption and cost data enables ESG reporting, cost optimization, and usage trend analysis.

Non-PO based invoices often arrive as attachments and are manually keyed in. Extracting vendor info, line items, tax details, and payment terms allows for faster accounts payable processing and reduced error rates.

Competitor product datasheets and specification documents contain valuable insights but are unstructured and hard to compare. A data extraction tool can structure this data, allowing automated benchmarking and feature comparisons.

Meeting notes are often shared as PDFs or scanned handwritten documents. Extracting key elements like attendees, decisions, and action items can improve task tracking and follow-up, especially in cross-functional teams.

Many R&D labs still use scanned lab notebooks or typed PDFs to store experimental records. Structured extraction of experimental setups, parameters, and observations can support better knowledge management and reproducibility.

Legal teams receive a large volume of correspondence in scanned or PDF form from external counsel, courts, or regulators. Extracting case numbers, parties involved, and deadlines can enhance legal document management systems.

Field inspectors often fill out handwritten forms or checklists which are scanned and emailed. Automating the extraction of date, location, findings, and photos can significantly improve field operations reporting and issue resolution.

Internal reports, especially those shared via PDF exports from BI tools, contain critical performance metrics. Automating the extraction of KPIs from these documents enables centralization and consistent performance tracking.

Safety audits use extensive checklists submitted as scanned documents or PDFs. Extracting structured information like compliance ratings, gaps, and corrective actions allows for trend analysis and audit closure workflows.

Project managers often submit status reports in varying formats. Extracting structured data on milestones, timelines, and budgets can feed into centralized PM tools, improving visibility and decision-making.

Product labels from competitors or suppliers contain claims, certifications, and ingredients that are often manually reviewed. Automating this can support competitive intelligence, regulatory checks, and innovation scanning.

Distributor agreements often contain complex pricing structures, discounts, and terms. Automating data extraction from these documents enables better pricing strategy alignment and compliance enforcement.

Customer onboarding often involves manually scanning and entering data from KYC documents, tax forms, or service agreements. Automating this ensures faster onboarding, data accuracy, and auditability.

Production batch records are often paper-based or PDF scanned documents containing lot numbers, process parameters, and yields. Extracting this data enables better traceability, compliance, and process optimization.

Maintenance teams receive work orders as handwritten notes or PDFs. Extracting task details, equipment IDs, and scheduled dates aids in better maintenance planning and resource allocation.

Incoming inventory receipts are often emailed as PDFs or scanned forms. Extracting SKU, quantity, and supplier details ensures timely inventory updates and reduces stock discrepancies.

Warehouse damage reports are often handwritten or emailed. Extracting details like product codes, quantities damaged, and damage cause allows accurate inventory adjustments and insurance claims.

Sales order acknowledgments from customers and partners come in unstructured documents. Extracting order numbers, delivery dates, and quantities enables faster order processing and customer communication.

Experiment logs and lab notes in R&D are often handwritten or stored in PDFs. Extracting parameters, results, and observations supports faster analysis and IP documentation.

Audit reports from suppliers come as lengthy PDFs with mixed content. Extracting key findings, non-compliances, and corrective actions enables better supplier risk management.

Incident reports for quality issues are often filed manually. Extracting incident details, root cause, and corrective action accelerates investigation and resolution.

Calibration records are kept as PDFs or scanned forms. Extracting dates, results, and next calibration due dates supports compliance and maintenance scheduling.

Inbound shipment documents are received as PDFs and emails. Extracting shipment details speeds up receiving and inventory updating.

Warranty claims are submitted on paper or PDF forms. Extracting customer info, product details, and claim reasons facilitates faster claims processing.

Attendance sheets for employee training are often paper-based. Extracting names, dates, and completion status enables better HR compliance tracking.

Customer feedback forms collected via paper or scanned formats are hard to analyze. Extracting responses enables sentiment analysis and quality improvement.

Sales reports contain commission details that are manually extracted for payroll and incentive calculations. Automating this speeds up payroll and reduces errors.

Supplier invoices are received as PDFs or paper and need manual entry for accounts payable. Extracting invoice data enables faster payment cycles.

Employee expense reports submitted as PDFs or scanned receipts are manually processed. Automating extraction improves reimbursement speed and accuracy.

Compliance audits use paper or PDF checklists that must be manually reviewed. Extracting checklist status and comments accelerates compliance reporting.