Solution

Document Processing Automation

Automatic extraction of structured data from invoices, contracts and forms, with a defined review step for anything the extraction is unsure about.

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How we work

Document automation takes over from someone who opens a PDF, reads it and types the numbers into another system. Done well, it extracts the vendor, amount and line items from an invoice, routes a contract to the right approver based on its content, and flags the few documents it is unsure about for a person to check instead of guessing and moving on.

This is distinct from broader business process automation. The work here is specifically about documents: reading them accurately regardless of format, classifying what kind of document they are, and getting the extracted data into the systems that need it.

Scope

Core features

OCR and data extraction from scanned documents
Text and structured fields get extracted from scanned PDFs and images, turning a document that used to require manual reading into structured data a system can use directly.
Document classification
Incoming documents get automatically sorted by type, such as invoice, contract, or identification document, so each type can be routed through the correct extraction and approval process.
Template-based document generation
Contracts, proposals, and other outgoing documents generate automatically from a template and structured data, replacing a manual copy-and-edit process for routine documents.
E-signature integration with an audit trail
Documents route for signature with a full audit trail of who signed, when, and from where, integrated directly into the same workflow that generated and routed the document.
Approval routing based on document content
A contract above a certain value or an invoice from a new vendor routes to the right approver automatically, based on rules applied to the extracted data itself.
Confidence scoring with human review
Every extracted field carries a confidence score, and anything below a set threshold routes to a person for a quick check instead of being trusted automatically.
A searchable document archive
Processed documents and their extracted data are stored in a full-text searchable archive, replacing a shared drive full of PDFs nobody can search by content.
Integration with existing systems
Extracted data pushes directly into your ERP, accounting platform, or CRM, so the automation removes the manual entry step rather than just producing a cleaner PDF.

Architecture

Choices that shape the build

OCR accuracy and where human review belongs
No extraction pipeline is perfectly accurate on messy real-world documents, so the system is built around a confidence threshold that routes uncertain results to a person rather than assuming every extraction is correct.
Handling unstructured and varied document formats
Real invoices and forms rarely follow one template, especially across many different suppliers, so extraction models need training and testing against your actual document variety, not a clean sample set.
Extraction accuracy drift over time
Accuracy on a specific document type can drift as new senders or formats appear, so accuracy gets monitored on an ongoing basis rather than validated once at launch and assumed to stay stable.
Legal validity of e-signatures
E-signature workflows are built to meet the requirements of the ESIGN Act in the United States and eIDAS in the European Union, which govern what makes an electronic signature legally binding.
Document retention and audit requirements
Processed documents and their extraction history need a defined retention period and an audit trail, which matters for financial documents subject to review and contracts that may be referenced years later.
Secure storage for documents containing personal data
Documents containing personal or health information get encrypted at rest and access-controlled the same way any system handling that data would be, since document stores are an easy detail to overlook in a security review.

Build vs buy

When to build and when to buy

DocuSign and PandaDoc are the right call when the core need is e-signature and simple template-based document generation, and building that from scratch rarely makes sense given how mature those products are. Intelligent document processing platforms such as ABBYY or Hyperscience are worth licensing when extraction volume is high and the documents are a fairly standard type, like common invoice formats, since those platforms come with extraction models already trained on that kind of document.

Custom development earns its cost when documents are highly variable and specific to your industry, such as non-standard supplier invoices that do not match a general extraction model well, or when extracted data needs to flow directly into a proprietary internal system that off-the-shelf document platforms cannot integrate with cleanly.

Delivery

How delivery is phased

Catalog document types and accuracy needs
We collect real samples of every document type involved and define the accuracy bar each field needs to hit before it can be trusted without review.
Build the extraction and classification pipeline
Document classification and field extraction get built and tested against your real document samples, tuning the confidence threshold that decides what goes to human review.
Add review workflow and system integration
The human review queue and the integration pushing extracted data into your existing systems get built next. This typically takes several weeks depending on how many document types and systems are involved.
Pilot with real volume and launch
The pipeline runs against real incoming documents in parallel with the manual process before fully replacing it, so accuracy gets validated under real conditions rather than a curated test set.

Technology

Stack we usually choose

FAQ

Questions about Document Processing Automation

How accurate is OCR for extracting data from scanned invoices?

Accuracy depends heavily on scan quality and how standardized the invoice format is. Well-scanned, common invoice layouts often extract with very high accuracy, while poorly scanned or highly varied formats need a lower confidence threshold and more items routed to human review to stay reliable.

Can document automation integrate with our ERP or accounting system?

Yes. Extracted data, such as vendor, amount, and line items from an invoice, pushes directly into your accounting or ERP system through its API, so the automation removes the manual entry step rather than only producing a structured file someone still has to import.

Is DocuSign enough or do we need custom document automation?

If the need is mainly e-signature collection and simple template-based document generation, DocuSign or PandaDoc are usually sufficient. Custom automation is worth building when you also need data extraction from varied incoming documents or integration with systems those platforms do not connect to.

How do you handle documents that do not follow a standard template?

Extraction models get trained and tested against real samples of your actual document variety, not a single clean template, and a confidence threshold routes anything the model is uncertain about to a person for a quick check rather than a wrong automatic guess.

Are e-signatures collected through document automation legally binding?

Yes, when the workflow is built to meet the requirements of the ESIGN Act in the United States or eIDAS in the European Union, which includes capturing signer identity, intent, and an audit trail of the signing event.

Services

Services this draws on

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