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International Business Times
01-07-2025
- Business
- International Business Times
How Alberto Gimeno Sánchez Shaped the Future of Business Automation through Intelligent Document Processing
Alberto Gimeno is in a unique position today, as he stands in the middle of a technological change that promises to redefine how businesses handle their most tedious yet most critical operations. The Spanish mathematician-turned-entrepreneur has built his company, Invofox, into a powerhouse that processes millions of documents annually, transforming chaotic paperwork into organized digital information for over 100 companies worldwide. When Alberto Gimeno Sánchez relocated to San Francisco in June 2024, he carried with him more than just entrepreneurial ambitions. With him was the culmination of nearly a decade of technical experimentation, business failures, and hard-won insights about the persistent problem that plagues every modern office: the mountain of disorganized documents that required humans to decode. His company, Invofox, processes over 17 million invoices and documents annually across Europe and is rapidly expanding into North America, but the journey to this scale began with a simple observation about the inefficiency of manual data entry. "Just as Stripe transformed online payments and Twilio redefined communications by offering powerful APIs, Invofox is revolutionizing how businesses exchange document-based information online," Gimeno explains. The comparison is deliberate, as Stripe processes $1.4 trillion annually with a valuation exceeding $90 billion, while Twilio generates $4 billion in revenue with an $18 billion market cap. Gimeno sees document processing as the next infrastructure layer ripe for automation, and his company's trajectory suggests he might be right. The Mathematics of True Automation Alberto Gimeno's path to document processing began with dual degrees in Mathematics and Computer Science from Universidad Autónoma de Madrid. This academic foundation proved to be crucial when he co-founded his first startup in 2015, although it was the failures that he encountered that truly educated him about market realities. Before Invofox, he launched AlquilaLibros, a book rental service, and Whisper, a hardware security company focused on panic buttons. Each venture taught him something different about customer needs and market timing. The breakthrough came when Gimeno and his co-founder, Carmelo Juanes, recognized that artificial intelligence could finally solve what traditional Optical Character Recognition (OCR) had intended to but never fully delivered: truly intelligent document processing. While OCR systems read everything on a page, humans instinctively focus on what matters. Training AI to mimic this selective attention became Invofox's core innovation. The company's technology goes beyond simple text extraction, validating fields, autocompleting missing data, and catching errors that could cost businesses thousands of dollars per mistake. The technical architecture that Gimeno's team built handles the reception of millions of documents simultaneously, automatically splitting files, classifying document types, and scoring image quality. When a vendor fails to include their address on an invoice, Invofox automatically fills in the missing information. When tax calculations appear incorrect, the system flags potential errors before they propagate through accounting systems. This level of intelligence requires multiple AI models working in parallel, with the system determining which combination of technologies best serves each specific use case. Building the Appropriate Infrastructure for the Software Economy The business model Alberto Gimeno developed reflects his understanding that successful technology companies become an infrastructure rather than just an application. Invofox operates as an API-first platform, allowing software companies to integrate document processing capabilities directly into their existing workflows. Enterprise resource planning (ERP) solutions use Invofox to automate accounts payable processes, while payroll companies leverage the technology to migrate customers from competing platforms by automatically parsing historical employee data from payslips. This infrastructure approach has attracted over 100 clients globally, including notable names like Aon, Cegid, and Holded. The company has raised $11.2 million from European and American investors, with annual recurring revenue exceeding $3 million and growing at more than 10 percent month-over-month. The financial metrics reflect a business that has found product-market fit in a substantial market, but Gimeno's ambitions extend far beyond current performance. The expansion into the United States represents more than geographic growth. American software companies operate at different scales and have different compliance requirements from their European counterparts. Adapting Invofox's technology and sales processes for the US market required a full year of preparation, but early customers like Scripta Insights, aACE, and Repositrak demonstrate that the localization efforts have succeeded. The American market offers the potential for exponential growth, given the larger scale of enterprise software adoption and the higher tolerance for automation investments. Where Humans Belong in Automation Despite building technology that automates human tasks, Alberto Gimeno maintains that Invofox creates rather than destroys employment opportunities. His observations from client implementations suggest that automation actually changes how people work rather than eliminating their roles entirely. With the help of correct automation, accounting professionals who had previously spent hours on repetitive data entry can now focus on advisory services and strategic analysis. The technology enables them to offer more sophisticated and focused services to their clients, creating a competitive advantage. "We've implemented our technology with success across many clients, and as far as we know, no jobs have been destroyed by implementing Invofox. Instead, people change how they work," Infovox cofounder Carmelo Juanes notes. This perspective reflects his broader philosophy about artificial intelligence as an augmentation tool rather than a fearful replacement. The most successful implementations occur when companies view AI as enabling human expertise rather than substituting for it. The global compliance requirements that Invofox meets across the European Union and the US are evidence of the complexity of building a truly international infrastructure. Different countries have varying regulations about data processing, document retention, and financial reporting. Gimeno's team has obtained certifications that allow multinational corporations to use Invofox across their global operations without worrying about regulatory compliance in individual jurisdictions. Major Strides That Only Signal the Beginning As artificial intelligence continues to develop, Alberto Gimeno sees document processing as just the beginning of a broader change in how businesses handle information. The same principles that make Invofox successful, such as selective attention, error detection, and automated completion, apply to many other forms of unstructured data. The company's success in processing tens of millions of documents annually provides a foundation for expanding into adjacent markets where similar problems exist. For Alberto Gimeno and his partners, the goal remains constant: building the infrastructure that allows software companies to focus on their core business rather than the tedious work of extracting meaning from documents.
Time Business News
19-05-2025
- Business
- Time Business News
Document Processing: Unlocking Efficiency in a Digital World
In today's fast-paced business environment, organizations are inundated with an overwhelming amount of documents—ranging from invoices and contracts to forms and emails. Traditionally, processing these documents was a labor-intensive task, often fraught with human error and delays. However, the advent of modern document processing technologies has transformed how businesses handle information, providing tools that automate, streamline, and optimize document workflows. In this article, we will explore what document processing is, the technologies driving it, and how businesses can benefit from adopting these innovative solutions. Document processing refers to the set of activities that enable organizations to handle documents efficiently, from data extraction and classification to storage and retrieval. These activities can include: Digitizing physical documents (e.g., scanning paper documents into digital formats) (e.g., scanning paper documents into digital formats) Extracting key data (e.g., identifying relevant information such as names, dates, or amounts from scanned files) (e.g., identifying relevant information such as names, dates, or amounts from scanned files) Classifying and organizing documents into categories (e.g., invoices, contracts, receipts) documents into categories (e.g., invoices, contracts, receipts) Storing documents in secure, easily accessible systems in secure, easily accessible systems Routing documents for approval or further processing within business workflows Manual document processing can be slow and error-prone, especially when dealing with large volumes of paper or digital documents. However, by automating these processes with advanced technologies, businesses can drastically improve speed, accuracy, and efficiency. Modern document processing leverages a variety of cutting-edge technologies that allow businesses to automate the entire lifecycle of document management. Some of the most prominent technologies include: Optical Character Recognition (OCR) is one of the foundational technologies for document processing. OCR allows businesses to convert scanned images of text, such as invoices, receipts, and forms, into machine-readable text. This technology essentially 'reads' the text within images and translates it into a format that can be processed by computers. For instance, OCR is commonly used to automate the digitization of paper documents. A business receiving paper invoices can scan the invoices using OCR software, extracting key information such as the invoice number, total amount, vendor name, and due date. This information can then be automatically entered into the organization's accounting system, significantly reducing the need for manual data entry. Modern OCR tools can also handle more complex scenarios, such as recognizing handwritten text or dealing with poorly scanned documents. As OCR continues to evolve with machine learning, its accuracy and capabilities are improving, enabling it to handle a broader range of document types. Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on enabling machines to understand and interpret human language. In the context of document processing, NLP plays a critical role in analyzing and extracting meaning from unstructured text, such as emails, customer feedback, and contracts. NLP allows businesses to: Extract key information : Automatically identify and extract important details, such as customer names, product information, dates, or legal clauses from contracts or invoices. : Automatically identify and extract important details, such as customer names, product information, dates, or legal clauses from contracts or invoices. Classify documents : Automatically categorize documents based on their content. For example, a business could use NLP to sort customer inquiries, legal contracts, and purchase orders into separate folders. : Automatically categorize documents based on their content. For example, a business could use NLP to sort customer inquiries, legal contracts, and purchase orders into separate folders. Perform sentiment analysis: NLP tools can analyze the tone or sentiment of customer feedback, helping businesses understand customer satisfaction or identify potential issues. By automating text analysis and information extraction, NLP helps businesses process vast amounts of unstructured data quickly and accurately, making it easier to derive actionable insights from documents. Machine learning (ML) is another powerful technology used in document processing. ML allows systems to 'learn' from historical data, improving over time as they process more documents. In document processing, ML can be used to enhance a variety of tasks, such as data extraction, classification, and quality assurance. For example, an ML-based document processing system can be trained to identify specific data points, such as invoice totals or shipping addresses, from a range of document formats. As the system processes more documents, it becomes better at recognizing patterns, improving the accuracy of data extraction. Machine learning is also helpful in improving the system's ability to categorize documents. Over time, ML models can 'learn' the differences between various types of documents, such as contracts, financial statements, and shipping receipts, and classify them accordingly. Robotic Process Automation (RPA) refers to the use of software robots or bots to automate repetitive, rule-based tasks. In document processing, RPA can be used to automate a wide range of administrative tasks, such as data entry, document validation, and routing documents for approval. For instance, an RPA bot can be programmed to extract data from invoices, compare the information with purchase orders, and input the data into an enterprise resource planning (ERP) system. RPA can also be used to route documents to the appropriate departments for approval, ensuring smooth workflow management. By automating routine tasks, RPA frees up human workers to focus on more complex and strategic activities, helping businesses improve productivity and reduce operational costs. Adopting automated document processing technologies offers numerous benefits to businesses, ranging from improved efficiency to cost savings. Some of the key advantages include: Automating document processing drastically reduces the time it takes to handle documents. Tasks that once took hours or days can now be completed in minutes. For example, scanning and extracting data from invoices can be done automatically using OCR and RPA, saving employees valuable time. This increased speed accelerates decision-making and helps organizations respond to customer needs and business opportunities faster. Manual document processing is expensive in terms of both time and labor. By automating these processes, businesses can reduce their reliance on human resources, cutting operational costs. Additionally, by minimizing human errors, businesses can avoid costly mistakes, such as overpayments, missed deadlines, or compliance violations. Manual data entry is prone to human error, which can lead to costly mistakes and inefficiencies. Automated document processing, powered by technologies like OCR, NLP, and ML, significantly reduces the risk of errors, ensuring that data is accurately captured and processed. This increased accuracy not only improves business decision-making but also ensures that organizations remain compliant with regulatory requirements. In industries with strict regulatory requirements, such as healthcare, finance, and legal services, maintaining accurate and secure records is critical. Automated document processing helps businesses stay compliant by ensuring that documents are properly stored, categorized, and accessible for audits. Furthermore, document processing systems can be integrated with encryption and other security measures, ensuring that sensitive information is protected. As businesses grow, so do the volumes of documents they need to process. Traditional manual methods can quickly become overwhelmed, but automated document processing systems can easily scale to handle increasing volumes without adding extra resources. By leveraging technologies like RPA and ML, businesses can handle more documents without sacrificing accuracy or efficiency. Automated document processing is already being used across various industries to streamline workflows and improve operational efficiency. Some key sectors benefiting from these technologies include: Finance : Automating the processing of invoices, tax documents, and financial reports, enabling faster and more accurate financial management. : Automating the processing of invoices, tax documents, and financial reports, enabling faster and more accurate financial management. Healthcare : Streamlining the management of patient records, insurance claims, and medical forms, ensuring faster service delivery and improved patient care. : Streamlining the management of patient records, insurance claims, and medical forms, ensuring faster service delivery and improved patient care. Legal : Automating the categorization and analysis of legal documents, such as contracts, case files, and court orders. : Automating the categorization and analysis of legal documents, such as contracts, case files, and court orders. Human Resources: Improving the efficiency of employee onboarding, document management, and compliance tracking by automating HR-related paperwork. Document processing has become an essential component of modern business operations. By leveraging technologies such as OCR, NLP, machine learning, and RPA, businesses can automate time-consuming tasks, reduce errors, and improve efficiency. As the volume of data continues to grow, the adoption of automated document processing will only increase, helping businesses stay agile, cost-effective, and competitive in a data-driven world. Whether in finance, healthcare, legal services, or HR, these technologies are reshaping how businesses handle information and unlock new opportunities for growth. TIME BUSINESS NEWS
Hans India
16-05-2025
- Hans India
Chrome for Android Gets Smarter Text Zoom, Image Descriptions and Real-Time AI Captions
Google is making browsing and accessibility more seamless on Android with a fresh set of updates for Chrome and TalkBack. The most user-facing change? Chrome for Android now lets you zoom in on text without disrupting the layout of a webpage — a long-awaited improvement for mobile users. Previously, enlarging content on a page also zoomed in on images and menus, often causing formatting issues. With the latest update, users can simply slide to increase text size alone and apply it either per page or across all websites. To access the new Zoom feature, just tap the three-dot menu in the top-right corner of Chrome and adjust the text size slider. On desktops, Chrome's Optical Character Recognition (OCR) tool also gets a boost. It now automatically detects and processes scanned PDFs, making it easier to highlight, copy, search, and even use screen readers with these documents. The feature was earlier available in beta but is now widely rolled out for desktop users. Google is also improving accessibility on Android by deepening Gemini AI's integration with the TalkBack screenreader. TalkBack can now do more than just describe what's on screen — it can answer detailed follow-up questions about an image. Users can ask about colours, materials, or even what other elements appear in the photo. According to Google, this functionality helps provide "more contextual and nuanced information" to users with visual impairments. Another major update is the launch of Expressive Captions, a feature that brings real-time captions to most apps on Android phones. These AI-generated captions don't just display spoken words, but also convey how they're said — for instance, distinguishing between 'no' and 'noooooo.' The feature can also identify sounds like whistling or throat-clearing, making digital interactions even more immersive.
