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Inside Nutrient

A guide to the invisible work behind documents Introducing Nutrient Documents for Salesforce: Native document generation and signing Document AI vs. traditional OCR: Choosing between OCR, AI, and hybrid pipelines PDF SDK compliance and security evaluation checklist for enterprise teams (2026) Invariant Corp replaces paper processes with Nutrient Workflow and scales without limits What is process mapping? A complete guide Nutrient vs. Conga Composer for Salesforce document generation (2026) Document routing: How to automate document distribution The CTO’s AI playbook: Why accountability architecture beats orchestration Compliance workflow automation: Why built-in compliance is table stakes Workflow diagrams: Examples, symbols, and how to build one that actually runs Digital forms: Replace paper forms with automated workflows Approval workflow software: How to automate approvals Why document-centric automation is different The CEO’s AI playbook: Why decision architecture beats model selection Nutrient SDK product updates for Q1 2026 PDF redaction verification: How to prove sensitive data is permanently removed What is a VPAT? The complete guide to accessibility conformance reports What is PDF/UA? The accessible PDF standard explained Salesforce eSignatures: Generate, sign, and track documents in one flow Online document viewer: Options, tradeoffs, and how to embed one Document viewer for web apps: React, Vue, Angular (2026) Best document viewers in 2026: A buyer’s guide How to edit a PDF in Python: Add text, images, and annotations Nutrient advances Workflow platform with agentic AI for enterprise-grade speed and consistency in document-heavy operations How to create a Salesforce quote template from opportunity data The business case for accessibility: Five ways it drives enterprise value Python PDF library comparison (2026): 7 libraries for developers Why your AI agent hallucinates PDF table data PDF.js limitations: When to upgrade to a commercial PDF SDK How Subject scaled 5× with Nutrient’s PDF SDK without rebuilding its document layer I replaced our sales training with an AI coach that runs in Slack — here’s what broke Redirecting to: https://securitybuzz.com/cybersecurity-news/why-enterprise-permissions-are-ais-most-dangerous-inheritance/ Nutrient .NET SDK vs. iText Core: Complete comparison for .NET developers DocuVieware: Support’s most frequently asked setup questions Introducing Nutrient Workflow How to convert PDF to Word in C# (.NET) When email and spreadsheets stop working: Work order approval workflows for field teams on the move Compliance with confidence: Why document-centric automation is the foundation of your mission Nutrient expands AI Assistant, automating multistep document workflows inside any application What is document generation? A developer’s guide to PDF generation Document Converter data flow and how real-time watermarks skip the queue PDF/UA compliance guide: Requirements, standards, and best practices Computers still can’t understand you How Athena Intelligence built AI agents for regulated enterprises with Nutrient’s document infrastructure How to convert HTML to PDF (2026): 4 methods from browser print to SDK How to build a document extraction pipeline with Nutrient Vision API OCR vs. intelligent document processing: Choosing the right document extraction engine Beyond OCR: How document intelligence eliminates manual processing in regulated industries Nutrient vs. IronPDF: Complete comparison for .NET developers Nutrient vs. Aspose.PDF: Complete comparison for .NET developers Redirecting to: https://fortune.com/2026/02/19/openclaw-who-is-peter-steinberger-openai-sam-altman-anthropic-moltbook/ Lufthansa Systems uses Nutrient to deliver reliable, scalable PDF rendering for pilots worldwide Nutrient vs. Syncfusion: Complete comparison for .NET developers React’s useTransition: The hook you’re probably using wrong First City Monument Bank streamlines banking processes with Nutrient Workflow Redirecting to: https://www.sdcexec.com/warehousing/automation/article/22957364/nutrient-workflow-automation-the-missing-link-in-supply-chain-efficiency The complete guide to digital signatures: PAdES, CAdES, and XAdES explained Nutrient Python SDK: Production-grade document processing for Python Introducing agentic document editing for web applications with AI Assistant Nutrient vs. QuestPDF: Complete comparison for .NET developers How we fixed the GdPicture license expiration (and what to do if you’re affected) Red team security testing with agentic AI The future of healthcare document automation Best healthcare workflow software compared Nutrient SDK product updates for Q4 2025 How Harvey scaled legal document workflows 50 percent MoM without rebuilding infrastructure HIPAA-compliant document management in hospitals How we optimized rendering performance while handling thousands of annotations in React — Part 2 Automated PII removal with Nutrient API Redirecting to: https://www.devopsdigest.com/2026-low-code-no-code-predictions Redirecting to: https://www.kmworld.com/Articles/Editorial/ViewPoints/Leaders-predict-AI-to-continue-permeating-all-aspects-of-KM-in-2026-172594.aspx What are deep agents and how do they solve complex problems? 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A complete guide Enterprise PDF SDKs: Best PSPDFKit (now Nutrient) alternatives Nutrient SDK product updates for Q3 2025 GdPicture support best practices Redacting sensitive data with Nutrient AI redaction API How AI is transforming the customer experience at Nutrient: From instant answers to intelligent support
XtractFlow: AI-powered document processing engine
Jonathan D. Rhyne · 2024-01-23 · via Inside Nutrient

Table of contents

    XtractFlow: AI-powered document processing engine

    The ORPALIS team has been part of Nutrient since 2022, but we’d already begun working on document processing and machine vision years before, and as such, we’d experienced its limitations, such as the necessity for predefined extraction rules and rigid templates. Even with those limitations, the first intelligent document processing (IDP) technology offered business benefits when compared to manual processing; however, we’ve always believed we could achieve more with it — more accuracy, more speed, more agility, and more intelligence — and require less setup and tuning for each workflow.

    Today, we’re pleased to introduce the XtractFlow SDK and API from Nutrient — a generative AI PDF data extraction and intelligent document processing engine.

    XtractFlow simplifies IDP deployment by reducing it from days to hours, significantly reduces setup time for IDP workflows by eliminating the need for predefined rules or key-value pairs (KVPs), and enhances data extraction accuracy. Additionally, XtractFlow saves time and reduces complexity by enabling you to set document classification conditions and data extraction requirements using natural language.

    Core functionalities and use cases

    XtractFlow is an engine that operates as a headless processor that easily integrates with large language models (LLMs) like ChatGPT from OpenAI or Azure OpenAI. It’s designed to be compatible with most available LLMs, enabling you to select the generative AI provider that best meets your business needs.

    XtractFlow brings human-level accuracy and intelligence to document classification and data extraction in a way that many people have always expected.

    • AI-powered document processing — XtractFlow employs generative AI, using OpenAI and Azure OpenAI for document classification and data extraction in its current version.
    • Supports hundreds of formats — XtractFlow efficiently extracts data from hundreds of document formats, including PDF, JPEG, Office, and CAD files, regardless of document complexity.
    • Customizable, with robust data integrity — It features tailormade components and extensive validation rules for diverse industries, ensuring accuracy in data elements like postal addresses, bank account numbers, emails, and more.
    • Integration and compliance — XtractFlow is available as a .NET SDK that can be used to create a REST microservice or API suitable for global hosting, without storing documents or extracted content.

    The engine uses natural language as input for document classification and data extraction instructions. This means you can describe the types of data you want to extract and the documents to classify in the same way you’d express this information to a colleague. For example, you can say, “Extract the customer’s name, address, ID number, and signature date,” and XtractFlow will identify and extract the data, regardless of its location in a document.

    XtractFlow can categorize documents into predefined or custom semantic-based templates based on their content and structure. It easily classifies a variety of documents — including invoices, contracts, legal filings, medical records, and academic papers — from any unstructured document storage of your choice. This saves time by eliminating the need to set classification rules and identify the correct documents manually. Additionally, you can edit the predefined templates to adjust them for specific use cases.

    XtractFlow is built to extract a multitude of data. Examples include but aren’t limited to:

    Textual dataNumerical dataIdentification numbersWorkflow-specific data
    Names, addresses, emails, descriptive paragraphs, and other freeform fields.Dates, monetary values, quantities, statistical data, and other numerical information.Social Security numbers, account numbers, invoice numbers, employee IDs, and other alphanumeric identifiers.Various semantic text structures, such as insurance policy details, medical codes in healthcare, legal clauses in contracts, and educational qualifications.

    By utilizing generative AI, XtractFlow identifies and extracts data without the need for rigid extraction patterns, reducing reliance on traditional IDP technology. Generative AI significantly enhances efficiency and accuracy in any data extraction workflow, saving valuable time and effort.

    XtractFlow vs. traditional IDP

    XtractFlow delivers a quantum advance in simplifying deployment, implementation, and accuracy when compared to traditional IDP technologies. XtractFlow dramatically reduces the go-to-market time from days to hours, along with cutting down on the investment needed for IDP applications. It also simplifies setting up new classification and data extraction workflows, avoids the requirement for specialized skills or training, and boosts accuracy to prevent expensive errors.

    Traditional IDPXtractFlow
    Capability scopeExtracts prequalified/categorized entities and all key-value pairs.Extracts strictly and semantically predefined entities; suitable for defined key association tasks; faster development with NLP.
    Processing time and architectureHigh-performance processing speed when using tailored architectures and local inference.Flexibility to scale performance as needed based on the hardware selected.
    Accuracy and development timeLower initial accuracy (~70 percent on a predefined dataset), longer development time (~7 days), plus ongoing maintenance.High accuracy (>90 percent for invoices), with solution deployment within a day.
    Cloud-based vs. local inferenceAdaptable to both cloud-based solutions and local inference.Adaptable to both cloud-based solutions and local inference.
    Use case suitabilityBetter for extracting categorized entities or key-value pairs; suitable for more supervised approaches.Ideal for quick, accurate extraction of predefined/semantically defined information; versatile across a wide range of document templates.

    With its semantically driven instructions and no need to predefine extraction rules for specific document templates, XtractFlow overcomes the most challenging hurdles associated with IDP.

    1. Diverse format processing

      Simplifies the classification and extraction of data from various formats, including PDFs, Office files, and images.

    2. Unstructured data storage issues

      Streamlines the extraction of information from inconsistently stored documents (e.g. invoices mixed with contracts), including documents with varying structures and years.

    3. Challenges recognizing document type

      Improves accuracy in identifying and extracting data from a wide range of document types, such as applications, invoices, contracts, and patient intake forms.

    4. Complexity of targeting the correct data to extract

    While key-value pair extraction excels at retrieving defined data, XtractFlow addresses the complexity of extracting non-explicitly defined information.

    The core XtractFlow technology is built upon an access point design that has been specifically engineered to ensure long-term compatibility, regardless of the architectural changes in your solutions or the XtractFlow engine. This approach streamlines both the design and integration processes and greatly reduces latency for client-server applications.

    Advantages of XtractFlow over the ChatGPT API

    Many developers may wonder why they should use XtractFlow rather than the widely accessible ChatGPT API.

    While OpenAI’s ChatGPT adeptly processes documents, extracting pivotal data like invoice numbers and supplier details in JSON, XtractFlow also excels at processing speed, supplemented by advanced features such as document classification, ready-to-use models, and data validation. XtractFlow boasts several advantages, including enhanced privacy and security features, particularly with the upcoming local inference capability.

    XtractFlow represents a new era in designing IDP workflows using no-code components. This innovation makes integrating and utilizing the most powerful IDP technology easier and more cost-efficient than ever before.

    After three months in private preview, XtractFlow is now available for you to try for free. Our Solutions Engineer and Sales teams are always eager to address any questions you might have and provide a complimentary trial license, so please don’t hesitate to reach out.

    We’re leading a revolution to evolve the human experience with documents. Join us and stay ahead of the curve!

    To showcase the full potential of XtractFlow, we invite you to join our exclusive webinar on 8 February 2024 (17:00 CET/11:00 AM ET). This is a fantastic opportunity to see XtractFlow in action and understand how it can revolutionize your document processing workflows.

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