AI & Automation · Workflow Automation
Intelligent Document Processing (IDP)
Intelligent document processing is AI that reads your unstructured documents, invoices, contracts, forms, claims, and pulls the data out, classifies it, validates it, and sends it where it needs to go. Instead of staff keying values by hand, the system extracts them and flags only the low-confidence cases for a human to check. We build the pipeline that turns documents into clean, structured data.
Built withOCRNLPLLMsDocument AIHuman-in-the-loopValidation rulesData export
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What it is
What is intelligent document processing?
Intelligent document processing, or IDP, is the use of AI to turn unstructured documents into structured data. It combines optical character recognition to read text, natural language processing and large language models to understand it, and validation rules to check it, so an invoice, contract, or form becomes data your systems can use. The work is building that pipeline: classify the document, extract the right fields, confirm them, and route the result, with a person reviewing only the uncertain cases.
It matters most where documents arrive in volume and someone is keying them in by hand, with accounts-payable invoice processing the classic high-return starting point. IDP is distinct from robotic process automation: RPA follows fixed UI steps, while IDP comprehends the content and context of a document, even when the layout varies. When your data already arrives structured, you do not need IDP, and we will tell you so rather than over-engineering it.
What's included
What a document automation build includes
Document capture and OCRReading text from scans, PDFs, and images, including imperfect quality.
ClassificationSorting incoming documents by type so each one is handled correctly.
Data extractionPulling the specific fields you need, even when the layout varies by sender.
ValidationChecking extracted values against rules and source systems to catch errors.
Human-in-the-loop reviewRouting low-confidence results to a person, so accuracy stays high.
Routing and exportSending clean, structured data into your ERP, accounting, or database.
Audit and securityLogging every extraction and handling sensitive documents safely.
How we work
How we build document automation
1Sample your documents
We gather real examples of each document type to understand the variety.
2Define the fields
We agree exactly which values to extract and how they should be validated.
3Build the pipeline
We assemble capture, extraction, and validation with the right OCR and models.
4Set the review loop
We configure confidence thresholds so only uncertain cases reach a person.
5Test on real volume
We run a representative batch and tune extraction against your actual documents.
6Integrate and monitor
We connect the output to your systems and monitor accuracy after launch.
Why it matters
Why teams automate documents
IDP takes the manual keying out of document-heavy work and turns a backlog into structured data.
Less manual keying
Staff stop typing values from documents and review only the exceptions.
Faster turnaround
Documents are processed in minutes rather than waiting in a queue.
Cleaner data
Validation and review catch errors before they reach your systems.
Who this is best for
The right fit
Best fit when
You receive documents in volume, invoices, contracts, forms, or claims, and people are extracting the data by hand. A strong fit for finance, operations, and back-office teams where accounts-payable or onboarding paperwork is the bottleneck.
You might not need this
If your data already arrives structured through an API, database, or clean digital forms, you do not need document AI. See Custom API Integration to move and sync that data directly.
FAQs
Common questions about document automation
How is IDP different from basic OCR?
OCR only converts an image of text into characters; it does not know what those characters mean. IDP adds classification, field-level extraction, validation, and routing on top, using NLP and large language models to understand the document, not just read it. So OCR gives you raw text, while IDP gives you the specific, checked data your systems need.
How is document automation different from RPA?
RPA drives an application's user interface through fixed, predefined steps, which works when the screens and layout are stable. IDP comprehends the content and context of a document, so it handles varying layouts and unstructured text that fixed steps cannot. They are often used together: IDP reads the document, and automation or integration moves the extracted data onward.
How do you automate invoice processing?
We capture each invoice, classify it, extract fields like supplier, line items, totals, and tax, validate them against your rules and purchase orders, and route the result into your accounting or ERP system. Low-confidence invoices go to a person for a quick check rather than being posted blindly. Accounts payable is usually the highest-return place to start because the volume and the manual effort are both high.
Can AI read documents it has never seen before?
Modern IDP using large language models can extract data from new layouts without a template trained for each sender, which is a major shift from older template-based tools. That makes it practical for documents that vary widely, like invoices from many suppliers. We still test against your real documents and set review thresholds, because no extraction is perfect on every edge case.
How accurate is the data extraction?
Accuracy depends heavily on document quality and the field being extracted, so we do not quote a single headline figure. Instead, we measure accuracy on your actual documents during testing and set confidence thresholds, so anything uncertain is routed to a human rather than passed through wrong. That review loop is what keeps the data you rely on trustworthy.
What happens to documents the AI is unsure about?
They are flagged by confidence score and sent to a person to confirm or correct, which is the human-in-the-loop step. The system follows your field definitions consistently, but you stay in control of the uncertain cases. This keeps throughput high on the easy documents while protecting accuracy on the hard ones.
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Drowning in documents?
Get a free automation audit. We will look at your document types and volume, show you where IDP pays off fastest, and scope a pipeline before you commit, with no invented accuracy promises.
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