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Intelligent Document Processing (IDP) Platform

super.AI is AI document processing software for operations teams: an intelligent document processing platform that classifies documents and extracts the fields you need. Configure human-in-the-loop (HITL) review steps for your own team, using built-in review views included on every plan.

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Trusted By Enterprises In Logistics, Shipping, Financial Services, And Technology Worldwide

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  • Saint-Gobain
  • Bureau Veritas
  • Balfour Beatty
  • Chi Cargo

Why teams choose super.AI for AI document processing

Generative AI for Documents

Solve document automation challenges using the latest Large Language Models (LLMs). Customize AI models and applications using your data faster than ever before.

The right model for each task

super.AI IDP breaks down complex processing tasks into simpler ones. Each task is routed to the AI model or software best suited to it. You can add review steps where your team needs to check the results.

Automatic Automation

AI and software results are combined into a unified output. When your reviewers correct a result, the workflow continues with that correction.

  • Target achieved: 96% automation rate
  • Triputra achieved: 98% automation rate

Quality, cost and speed targets you set

Users define desired quality, cost, and speed, then the platform selects the right combination of AI models and software. Your team can review results at configured review steps. Enterprise plans include contractual commitments.

  • Bureau Veritas achieved: 75% reduction in processing time · 80% cost savings on data entry · reduced error rate

Human review by your own team

Every plan includes built-in review views where your own reviewers can confirm or correct results at a configured review step. Managed review is not part of any plan. Any work by the super.AI Data Processing Crowd requires a separate signed agreement.

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Customer story

Powering the journey to zero-touch customer onboarding for Nexi Group

Payment technology leader Nexi Group faced challenges with slow, paper-based KYC and AML processes during merchant onboarding. By partnering with super.AI, Nexi significantly cut down manual review times during merchant onboarding, moving closer to their goal of a zero-touch, digital-first onboarding process and advancing their vision for a cashless Europe.

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Nexi Group headquarters

How AI document processing works in super.AI

Bring document intake, classification, extraction, review, and delivery into a connected process. The steps below show how AI and people handle the work from the incoming file to the output your team needs.

  1. Ingest documents and email attachments

    Start with a document from the work your team already handles, such as a PDF, a scan, an image, or an email attachment. Use email attachment scanning to forward invoices, purchase orders, contracts, and other incoming documents into the extraction and review workflow. Different supported attachment types can follow the same workflow instead of requiring a separate tool for each format.

  2. Classify and separate documents

    Document classification organizes incoming files by type so a mixed batch can move into the appropriate extraction and review steps. When a PDF contains multiple invoices, document splitting can separate them into individual files. That keeps document sorting connected to the work that follows, rather than leaving reviewers to organize every file first.

  3. Extract the fields and tables you need

    Extract the fields your process needs, including the rows and columns inside tables in invoices, packing lists, and financial reports. Table recognition handles nested headers, merged cells, and layouts spread across multiple pages without templates for each layout. LLM intelligence adds contextual reasoning to OCR and document extraction for information that needs to be understood in context.

  4. Review low-confidence results

    You can configure a review step for low-confidence results. Your reviewers can confirm or correct values in the review view, and the workflow continues with their corrections. Managed review is not part of any plan. Any work by the super.AI Data Processing Crowd requires a separate signed agreement.

  5. Validate and deliver the output

    Validate extracted values against the checks your process requires before delivering the output to its next destination. Send structured data to CSV, JSON, or Google Sheets, or use integrations and the API to pass data to business systems. If the workflow includes sensitive information, document redaction can remove relevant information from a page, a document, or a collection before it is shared.

With Flows, describe the document work in plain language, see each step the platform builds, and connect capture, extraction, review, and delivery in one workflow.

Keep your data secure and compliant

super.AI offers enterprise-grade security.

SOC 2 compliant
GDPR compliant
  • Support SOC 2 and GDPR compliance
  • Granular role and user management
  • Detailed audit trails and logs for each document
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Intelligent document processing solutions by use case

Explore how classification, extraction, and review fit the documents your team handles, from onboarding and loan applications to purchase orders, invoices, insurance claims, and shipping paperwork.

How to evaluate intelligent document processing software

Start with representative documents from your own queue, including scans, varied layouts, and the files people currently correct by hand. Ask whether the software can handle those differences without a template for every layout, then compare the fields that still need manual review.

Look closely at the review workflow. Check how uncertain values reach a person, how corrections are recorded, and what happens before those results leave the platform. Confirm that validation can use the checks your downstream process needs, rather than judging extraction in isolation.

Review security documentation, access controls, and audit trails with the people responsible for your data. Ask which OCR and language models can be used for each task, and how model choice fits your document types. Finally, confirm the output formats and integrations your team needs to make the extracted data useful.

Use the intelligent document processing software buyer's guide to compare starting options, review requirements, and delivery needs, then test the same real files before you choose.

Additional IDP Resources

Compare document automation approaches

Explore how different approaches handle document processing, then plan your workflow with Flows.

Frequently Asked Questions

Intelligent Document Processing (IDP) is document processing software that uses multiple artificial intelligence (AI) and machine learning (ML) technologies to classify and extract data from business documents, enabling end-to-end process automation.

First-generation IDP put a modern interface on top of OCR and used AI and ML to extract data from the OCR output. super.AI, a next-generation IDP platform, builds review and correction into the workflow. Every plan includes built-in review views where your own reviewers can confirm or correct results at a configured review step. The flow continues with their corrections. You set the quality, cost, and speed targets. Managed review is not part of any plan. Any work by the super.AI Data Processing Crowd requires a separate signed agreement.

IDP solutions are designed to only process documents. UDP solutions on the other hand offer a unified AI platform that is able to process any unstructured data type: documents, images, videos, audio, and text.

Optical Character Recognition (OCR) has been used to digitize scanned documents for decades. Later iterations of OCR solutions allowed users to extract data from digitized documents using templates that defined the position of fields in various documents. These solutions worked well for the structured documents but required a lot of setup and maintenance for semi-structured documents such as invoices and purchase orders.

IDP solutions are modern solutions designed for business users to extract data from structured and semi-structured documents. They use AI and ML to classify and extract data from documents digitized using OCRs to deliver higher accuracy at a lower cost.

Document AI is another name for modern cloud-based OCR solutions that leverage AI and ML to improve the quality of document digitization. IDP solutions are built on top of OCR and Document AI solutions to classify and extract data from documents.

super.AI IDP combines the latest AI models with human-in-the-loop review by your own reviewers in built-in review views, quality thresholds you define, and an open architecture that lets you plug in best-of-breed OCR / LLM models per task, making it more flexible than first-generation IDP. Managed review is not part of any plan. Any work by the super.AI Data Processing Crowd requires a separate signed agreement.

AI document processing is another name for IDP. Both describe software that uses artificial intelligence and machine learning to classify documents and extract their data, so the terms are interchangeable. super.AI IDP is AI document processing software that pairs the latest AI models with human-in-the-loop review.

Data capture solutions were earlier document classification and extraction tools. They used regular expressions to classify documents and templates to extract data from structured and semi-structured documents. IDP replaces fixed rules and templates with AI and ML, so it can handle documents whose layout varies.

IDP solutions use a combination of computer vision, document AI, OCR, fuzzy matching, machine learning, supervised learning, and/or active learning to classify and extract data from documents.

IDP solutions include some of the following components. Pre-processors improve the quality of scanned documents with techniques such as deskewing, binarization, and noise reduction; modern cloud OCR and document AI solutions now include this natively. A digitizer uses one or more OCR or document AI solutions to digitize the documents. A classifier identifies the type of each document. A router, found in some UDP and next-generation IDP solutions, breaks document processing into pieces and sends each one to the AI best suited to it. An extractor uses AI and ML to pull the required data from digitized documents. A post-processor uses rules and ML to validate and enrich the extracted data. A combiner merges output from multiple sources into one structured result. A trainer uses supervised or active learning to learn from human reviewers and raise automation rates over time.

super.AI IDP is designed to process any type of document: structured, semi-structured, or unstructured. It can process handwritten notes and understand signatures, logos, and stamped approvals.

IDP solutions, including those from super.AI, can handle multiple document formats, including digital and scanned PDFs, TIFF, GIF, JPEG, PNG, and more.

Many IDP solutions, including super.AI, can classify documents automatically, sorting heterogeneous batches into categories.

Some IDP solutions can process handwriting. However, the capabilities vary widely. Some only handle block text; others can handle cursive. Since super.AI has an open architecture, it can be customized to use the best document AI or OCR solutions for handwriting in a given language.

Intelligent Document Processing (IDP)

Automate information extraction from any business document, with built-in human-in-the-loop review by your own team.

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