Organizations don’t lack data—they lack usable data. In many enterprises, some of the most valuable information still lives in unstructured documents: invoices, purchase orders, delivery notes, KYC forms, HR files, contracts, claims, inspection reports, and compliance submissions. These documents arrive as PDFs, scans, images, emails, and attachments—often in inconsistent formats. When teams rely on manual reading and data entry, processes slow down, costs rise, and errors creep into decision-making.
This case study describes how Maayan Technologies implemented Intelligent Document Processing (IDP) at scale—transforming high-volume PDFs into validated, decision-ready data integrated directly into business workflows.
A multi-location enterprise was processing tens of thousands of documents each month across finance, operations, and compliance. Despite using modern enterprise systems, document-driven workflows still depended on manual effort.
The client faced five core problems:
- High manual workload and rising costs
Operations teams were spending hours extracting fields, verifying values, and keying data into ERP/CRM systems. Peak volumes created backlogs, delayed approvals, and increased overtime. - Inconsistent document formats
Documents came from hundreds of vendors and partners—each with different templates, layouts, languages, and scan quality. Rule-based extraction tools struggled, and accuracy was unpredictable. - Errors and downstream rework
Small extraction mistakes (invoice totals, GST numbers, bank details, item codes) caused payment holds, duplicate records, and reconciliation issues—leading to rework and vendor disputes. - Slow decision cycles
Documents were “processed” but not truly “understood.” Teams lacked confidence in the extracted data, so decisions still required human verification. - Compliance and audit challenges
Document handling across email, shared drives, and spreadsheets made it difficult to prove controls. Tracking who approved what and when was inconsistent, creating audit pressure.
The organization needed an IDP platform that delivered not only extraction—but business-grade accuracy, governance, and workflow automation.
Maayan Technologies deployed an end-to-end IDP capability designed for high throughput, strong validation, and operational adoption—so documents could move from inbox to action with minimal friction.
1) Multi-Channel Document Ingestion
We enabled standardized intake from email, portals, shared folders, and system integrations. Documents were automatically tagged with metadata (business unit, vendor/customer, source, and document type), creating a structured pipeline from day one.
2) Document Classification & Smart Routing
Using ML-based classification, the system identified document types (invoice, PO, GRN, KYC form, contract, claim, etc.) and routed them to the correct workflow. This removed the first major manual step: sorting and forwarding.
3) Extraction with Context-Aware Models
Instead of relying only on fixed templates, we used context-aware extraction that handled variations in layout and language. For each document family, key fields were extracted—such as:
Header fields (invoice number/date, supplier, tax IDs, payment terms)
Line items (SKU, description, quantity, unit price, tax, totals)
Banking and compliance fields (IFSC, account, PAN/GST, signatures, stamps)
4) Validation Layer: “Trust but Verify”
Accuracy at scale depends on validation—not just extraction. We implemented business rules and cross-checks such as:
PO vs invoice matching (3-way match readiness)
Tax calculations and rounding tolerance checks
Duplicate detection (invoice number, vendor, amount combinations)
Mandatory field completeness and format validation
Vendor master and customer master verification
This reduced false positives and prevented bad data from entering core systems.
5) Human-in-the-Loop for Exceptions
For low-confidence fields or complex documents, the system created a review task with highlighted evidence. Reviewers corrected only what needed attention, not the entire document. Their corrections improved the model over time, reducing exceptions month by month.
6) Workflow Automation and System Integration
Extracted and validated data was pushed into ERP/CRM/workflow tools automatically—triggering approvals, payment cycles, onboarding steps, or compliance actions. This turned document processing into “document-driven automation,” not a standalone scanning exercise.
7) Dashboards, Governance & Audit Trails
We delivered operational dashboards tracking throughput, accuracy, exception rates, cycle time, and backlog. Every step was logged for auditability: who reviewed, what changed, and which rule triggered an exception. Access controls ensured sensitive documents were protected.
The IDP program shifted document handling from a manual effort to a decision-ready pipeline:
Faster processing cycles with automated intake, classification, and extraction—reducing bottlenecks during peak volumes.
Higher accuracy and lower rework through validation rules and exception-based review rather than full manual entry.
Improved compliance readiness with complete audit trails, standardized controls, and secure document access.
Better operational visibility through dashboards and SLA tracking across teams and locations.
Scalable foundation to add new document types, vendors, and workflows without restarting the program.
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