Intelligent document processing & OCR
Extract, classify and validate information from invoices, forms, PDFs and scanned documents, with review queues and connections to business systems.
THE BUSINESS CONTEXT
Documents often arrive in formats that do not match the system where staff need to enter them. Copying fields by hand takes time, and errors can propagate into purchasing, accounting and customer records. Intelligent document processing creates a structured path from a file to a reviewed record.
We begin with representative documents and the fields that matter to the receiving workflow. Text recognition, AI extraction and deterministic checks work together. Every proposed value should be traceable to the original document where practical.
YOUR FIRST ENGAGEMENT
Focused Pilot
Process one document family into a reviewer queue and an approved structured export.
Discuss This PilotRepresentative authorised files, target fields, validation rules and a reviewer who knows the process.
Measures are agreed for your project. Results depend on the data, workflow and evaluation; they are not guaranteed improvements.
WHAT WE DO
Collect authorised examples covering clean PDFs, scans, layouts, languages and edge cases. Define the required fields, tables and document classifications. OCR quality depends on input quality; handwritten notes and poor scans may need a separate feasibility check. Sampling the difficult cases early helps set useful acceptance criteria.
Read text and tables, normalise dates and units, and retain page or region references. Distinguish a missing value from a guessed value. Document text is treated as input to be interpreted, not as instructions that can change the system’s behaviour. Extraction formats are versioned to match downstream applications.
Validate totals, required fields, reference numbers and duplicates against approved rules. Route mismatches and uncertain results to a reviewer with the original file visible. Confidence signals are tested against real errors; a model’s self-reported certainty is not accepted as proof that a field is correct.
Export reviewed data to CSV, a database, an ERP or a business application through authorised interfaces. Track document status and prevent repeated processing from creating duplicate records. Retention, deletion and access settings apply to both original files and extracted information.
A DEFINED ENGAGEMENT
Your proposal defines the exact scope, responsibilities, milestones, and exclusions. Depending on the engagement, the work can include:
WHERE IT FITS
Prepare invoice records for checking and posting.
Structure application forms and service documents.
Compare supplier quotes and supporting documents.
WHO THIS CAN HELP
Explore example workflows and the customer groups these services are designed to support.
A PRACTICAL FIRST STEP
Choose one useful task, agree how the result will be checked, and use the evidence to decide what should happen next.
QUESTIONS, ANSWERED
Potentially. We evaluate scan quality, language and document variation on a representative sample before committing to a scope.
Exceptions are expected. The pilot establishes which documents can follow an automated path and which need review, based on measured field accuracy and business rules.
Yes, table extraction can be included. Multi-page tables, merged cells, unit differences and handwritten changes need dedicated examples and validation.
CONNECTED CAPABILITIES
Assist finance teams with invoice checking, reconciliation suggestions, collections drafts and management reporting while preserving approval controls..
Explore This Specialty
Build AI tools for supplier enquiries, quote comparison, purchasing documents and supply-chain exceptions, connected to approved operational data..
Explore This Specialty
Prepare documents and business data for AI with reliable ingestion, data-quality checks, access controls and repeatable update pipelines..
Explore This SpecialtyA CONVERSATION IS A GOOD PLACE TO START