In many organisations, critical data hides inside documents: contracts, invoices, emails or reports. This information is often unstructured - every document looks different, and the fields required are not laid out in uniform tables or forms. Traditional approaches to automatically reading such documents required painstaking template creation, training ML models, or relying on manual data entry. Today, however, we are witnessing a breakthrough. Generative artificial intelligence can “read” documents almost as a human would, then extract the important information based on a description alone, without any need for prior rule-building. The latest solution from UiPath - the Intelligent Xtraction and Processing (IXP) platform - harnesses this technology, offering generative data extraction from documents. This functionality is already available in Europe and the US as part of the IXP service, which means Polish and other European organisations can use it without restriction. Let us look at how this innovative mechanism works and what benefits it brings to business.
What Is UiPath IXP?
UiPath IXP (Intelligent Xtraction and Processing) is a new, comprehensive platform for intelligent document and communications processing. It combines the existing capabilities of Document Understanding (classic document processing) and Communications Mining (analysis of communications content, such as emails or tickets) with an entirely new, prompt-based method of extracting data from unstructured, complex documents. Put simply, IXP can turn disorganised text data into structured information ready for use in business processes. The platform identifies and extracts key information from documents or messages, enabling full automation of tasks that were previously beyond the reach of machines. Importantly, IXP is a multimodal solution - it handles a variety of data formats, including text, tables, and even graphical and image elements. The X in the name IXP represents this universality (“Xtraction” rather than “Extraction”) and the ever-expanding range of content types the platform can process.
Generative extraction is precisely the newest element of the IXP ecosystem, designed for unstructured and highly complex documents. Traditional tools required pre-defined fields or training models on hundreds of examples of a given document type. The generative approach is different - the system uses a large language model (LLM) to understand the content of a document and respond to the user’s instructions (so-called prompts) about what to extract. This makes it possible to retrieve the data needed simply by formulating a question or instruction in natural language. IXP identifies and extracts information based on a descriptive instruction, without the need to train dedicated models for every document format. This approach eliminates lengthy preparation - time-to-production is significantly shortened thanks to the use of ready-made AI models and contextual learning techniques such as retrieval augmented generation.
Generative Extraction - How It Works and What It Can Do
Generative extraction in IXP harnesses the power of AI based on language models to “read out” specific information from a document. It works in a manner similar to conversing with an intelligent assistant: the user defines what data is needed, and the model itself locates it within the document’s content. Crucially, this solution operates at runtime - that is, during document processing - without any prior training for a specific pattern.
This generative approach is particularly effective where documents are long, inconsistent, or have a non-standard layout. IXP can handle documents in which data has no fixed location or format, appearing, for example, across multiple tables, extensive continuous text, bulleted lists or embedded graphics. This opens the door to automation for documents that were previously too “chaotic” for typical algorithms. A 100-page annual report? A medical report full of descriptions? A scanned contract with diagrams and charts? The generative model is able to understand the context of such complex content and extract the key facts from it.
It is worth emphasising that IXP was also designed with visual elements and handwriting in mind. By combining OCR technology with language models, generative extraction can handle even scanned documents, photographs of forms, or hand-filled invoices. For example, it can analyse a photographed, handwritten invoice and correctly read elements such as the date, the amount, or the company details. This represents enormous progress - previously, reading handwriting required specialised tools and often produced errors. Now, using advanced AI models, the system learns context: it understands that, for instance, a string of digits next to the word “Date:” represents the document’s issue date, not a random number.
Examples of Applications
The potential applications of generative extraction are very broad, which makes this technology attractive across a range of industries. Here are a few examples of documents and areas where IXP delivers particular value:
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Finance and banking: automated analysis of credit applications, bank statements or financial reports - the model can pick out key numerical and textual data from long documents (such as totals, dates, entity names).
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Insurance: processing insurance policies, applications and claims - even if every policy has a different layout, the AI understands general concepts (insured party, scope of cover, sum insured) and extracts them.
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Legal: analysis of contracts, legislation, and pleadings - the model is able to find key clauses, dates, parties to an agreement or contractual penalty amounts within lengthy legal documents. This can significantly speed up the work of legal departments.
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Healthcare: reading medical referrals, test descriptions, and hospital discharge summaries - IXP can automatically capture diagnoses, prescribed medications and patient recommendations, even where these are written in narrative form within a discharge report.
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Sales and customer service: analysis of order forms, complaints and email correspondence from customers - generative AI extracts, for example, an order number, the subject of a complaint, or preferred contact details, streamlining the automated handling of enquiries.
Of course, these are only a selection of scenarios. Wherever unstructured text data exists, there is potential for its automatic use. Importantly, this new IXP capability does not replace existing methods, but complements them. For simpler, structured documents (such as typical electronic invoices or forms), classic Document Understanding models, trained on a specific layout, remain sufficient in many cases. Generative extraction, however, steps in where classic models reach their limits - offering flexibility and intelligence in handling previously unknown formats.
Business Benefits
Why exactly is generative extraction generating so much excitement in the business world? Here are the key benefits organisations can expect from deploying this technology:
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Automation of previously inaccessible processes: Organisations can automate an area of document processing that previously required human involvement. What was once a “blind spot” for automation (such as unusual correspondence from business partners or hand-filled forms) can now be handled by software robots. This translates into an expanded scope of processes running without manual intervention.
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Time and cost savings: Generative AI can process a document in seconds, while an employee would need minutes or hours. At scale (hundreds of documents daily), this represents enormous time savings. Employees can focus on higher-value tasks instead of laboriously entering data. Less manual work also means lower operating costs.
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Greater accuracy and data consistency: Automated reading eliminates many human errors - typos when entering figures, overlooked sections of text, and so on. Generative models achieve high extraction precision thanks to their contextual understanding. What is more, they operate consistently according to once-defined guidelines (prompts), ensuring consistency in the information extracted over time.
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Faster decision-making: With key data automatically extracted in structured form (for example, a table with the most important fields from a 50-page contract), decision-makers can analyse it immediately. The time between obtaining information and taking business action is shortened. For example, instead of reading an entire financial report, an analyst is immediately presented with the key indicators and trends in bullet-point form.
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Flexibility and scalability: Because there is no need to build a separate model for each document type, the solution is easy to scale to new use cases. It is enough to define new queries/instructions for the AI when a new document type appears in the organisation - without a long wait for deployment. This is especially important in a dynamic business environment, where speed of implementing change can be decisive.
SNOK’s Role in Document Automation
As SNOK, we have observed for years the challenges our clients face in processing unstructured data, and we actively seek ways to address them. Thanks to our experience in AI and process automation, and close cooperation with partners such as UiPath, we had already explored this area and prepared for the arrival of generative extraction techniques. SNOK took part in trials and pilot deployments of solutions based on large language models for reading documents - before this technology entered the mainstream. We have delivered projects using classic Document Understanding enhanced with elements of generative AI, for example, to analyse non-standard financial documents. This experience allows us to move smoothly into the IXP era.
“Generative AI is becoming the key to unlocking data trapped inside documents. We have seen how organisations have struggled with hand-filled invoices or inconsistent reports. Today, thanks to technologies such as IXP, this difficult, analogue data can be automatically transformed into digital business information. This is a qualitative leap in automation, translating into a real competitive advantage for organisations,” says Jacek Bugajski, CEO of SNOK.
Our company already helps clients implement intelligent document reading - from selecting the right models and strategy (when a classic trained model is preferable, and when a generative one is better suited), to integrating the solution with existing workflow systems. As a UiPath partner, we provide full support in leveraging the IXP platform: from the proof-of-concept phase, through team training, to maintenance of the working solution. This allows organisations to safely and effectively harness the potential of generative extraction, achieving a swift return on investment through the automation of further processes.
Summary
Generative document extraction marks the next stage in the evolution of automation - a stage in which machines learn to understand the unstructured world of data. UiPath IXP delivers a tool that, just a few years ago, remained the stuff of dreams: a universal information extractor that operates through a free-form dialogue with a document. For business, this means the ability to harness a vast amount of data that was previously practically inaccessible to digital processes. Organisations that embrace this technology gain an advantage - their processes become faster, cheaper and more scalable, and employees can focus on analysis and decision-making instead of sifting through stacks of paper.
Is your organisation ready for this revolution in information processing? If so, UiPath IXP, combined with generative AI, is the tool that will let you step into a new era of automation. SNOK, as a trusted technology partner, is on hand to support the implementation of these innovative solutions. See for yourself how generative extraction can transform the day-to-day operations of your organisation - this is no longer the future, it is happening here and now. Unstructured documents have just stopped being an obstacle and become another resource that can be effectively harnessed for business growth.