HITL (Human-in-the-loop) verification plays a crucial role in the IDP pipeline by addressing edge cases, ensuring accuracy when automated systems encounter uncertain or complex data, or for resolution when pre-defined validation rules are not met.
Human-in-the-loop verification
HITL verification combines human expertise with automated processes to ensure AI system decisions are accurate and aligned with business goals. By integrating human reviewers at critical decision points, this approach enhances precision, reduces errors, and builds trust in AI-driven workflows.
Human oversight plays a key role in validating AI results, ensuring reliability and acting as a crucial safety net for high-stakes tasks where errors can be costly or sensitive. Additionally, the input from human experts contributes to continuous learning and model optimization, enabling the AI to improve over time and adapt to evolving business needs.
Humans verify AI-driven insights, minimizing false positives or negatives.
Streamline processes by delegating repetitive tasks to AI and reserving human input for complex decisions.
The combination of automation and human review assures stakeholders of reliable outcomes.
Leverages human expertise strategically to manage increasing data volumes without sacrificing accuracy.
AI systems evolve through ongoing data input and human feedback, ensuring consistent improvement and adaptability.
An out-of-the-box manual verification UI and workflow promote efficiency by providing a streamlined interface for human experts to quickly review and validate AI-processed data.
AI systems process large volumes of data, flagging cases that require further attention.
Subject matter experts review flagged data, ensuring alignment with business objectives and accuracy standards.
Expert insights are fed back into the AI to improve its learning and future decision-making. This cyclical process ensures continuous improvement and consistency in outcomes.
For many organizations, the question isn’t whether to invest in AI innovation, but when and how. In this article Ulf Persson, CEO of ABBYY, discusses the findings of our State of Intelligent Automation Report.
OCR solutions have come a long way, incorporating AI, machine learning, and natural language processing to deliver modern intelligent document processing solutions—capable of understanding and extracting data from any document.
This comprehensive demonstration of the Quality Analytics dashboard in ABBYY Vantage shows how you can track the chain of documents that are being processed without human intervention over time (straight-through processing rate). Key points include tracking document processing, optimizing human-in-the-loop resources, adjusting data verification settings, and analyzing extraction accuracy.
Image enhancement
Human in the loop & continuous learningIngest documents from multiple channels—mobile devices, email, shared folders, network scanners, and direct connections to business systems via API or pre-built connectors—ensuring seamless integration into your workflows, no matter how documents enter your organization. This flexibility empowers you to efficiently support diverse business processes, adapting to your specific needs and streamlining operations from every entry point.
The quality of document images can vary significantly due to issues like poor lighting and distortions from mobile cameras—or come with multiple auxiliary elements such as patterned backgrounds, protection marks, field markings, lines, and guides that obscure important information.
ABBYY’s AI-powered image enhancement algorithms optimize each image for accurate data extraction. The AI corrects distortions and separates text from the background, cleaning up even the most complex and visually busy documents—such as IDs, birth certificates, and forms—to achieve reliable results and high straight-through processing rates.
AI has transformed the ability to read and interpret content previously deemed impossible to process, dramatically expanding the use cases for automation. ABBYY IDP uses advanced AI-based optical character recognition (OCR) and intelligent character recognition (ICR) technologies to digitize printed and handwritten text, preparing it for further processing. These technologies are able to recognize the logical structure of the whole document, including complex elements such as tables, enabling document classification, data extraction, and high-quality export to digital formats.
Automate document classification and routing with AI classification models that analyze both text and image features through multimodal learning to recognize and organize documents. Once classified, documents are automatically assigned an AI extraction model for processing. By incorporating human-in-the-loop input, the models learn from user corrections and automatically adjust, continuously improving their performance over time.
Extract data from structured, semi-structured, or unstructured business documents using advanced AI and machine learning that mimic human understanding. ABBYY IDP reads and understands documents in over 200 languages and effortlessly handles complex tables, handwriting, checkmarks, barcodes, signatures, and more.
Automatic validation cross-checks information against databases and ensures compliance with built-in validation rules. Our low-code design approach gives you the flexibility to use pre-trained models available in the ABBYY Marketplace, tweak these ready-to-use models for the unique needs of your organization, or train custom models tailored to your specific documents.
Combine purpose-built AI with the flexibility of Large Language Models (LLMs) to enhance document workflows. This hybrid approach enables advanced summarization, contextual reasoning, and automated communication, unlocking new efficiencies in a secure and scalable environment.
Keep refining your processes through human-in-the-loop (HITL) review, which lets subject matter experts step in to manually check and correct document classes as well as extracted data through a convenient interface. This optional step is crucial when 100% accuracy is required or when a document doesn’t meet the specific validation rules established for each AI model. Each time a correction is made, the AI models improve through continuous learning and get more accurate.
The advanced quality analytics provided by ABBYY Document AI provide a clear understanding of your document processing performance and track improvements in straight-through processing rates over time. With actionable insights and tailored recommendations, you can pinpoint the root causes of problems and take effective actions to improve data extraction quality of the models for superior business outcomes within your IDP workflow.
ABBYY Document AI automatically exports data in the required format to meet your needs—whether JSON, CSV, XML, or others. The data is then sent seamlessly to your automation systems and business applications through simple REST API or pre-built connectors into your downstream processes.
Some businesses are aiming to deploy AI agents for simple, repetitive tasks where a rules-based system would be faster and more efficient understand why and how in this article.
AI Ethics Evangelist Andrew Pery recommends organizations bridge the gap between innovation and compliance by adopting a layered approach to AI regulation that strikes a balance between innovation and potential adverse impacts.
By combining memory, AI models, and systems integration, AI agents push automation further than ever before, showcasing how far we’ve come—and how much further we can go.
Some businesses are aiming to deploy AI agents for simple, repetitive tasks where a rules-based system would be faster and more efficient understand why and how in this article.
AI Ethics Evangelist Andrew Pery recommends organizations bridge the gap between innovation and compliance by adopting a layered approach to AI regulation that strikes a balance between innovation and potential adverse impacts.
By combining memory, AI models, and systems integration, AI agents push automation further than ever before, showcasing how far we’ve come—and how much further we can go.
Schedule a demo and see how ABBYY intelligent automation can transform the way you work—forever.
For many organizations, the question isn’t whether to invest in AI innovation, but when and how. In this article Ulf Persson, CEO of ABBYY, discusses the findings of our State of Intelligent Automation Report.
OCR solutions have come a long way, incorporating AI, machine learning, and natural language processing to deliver modern intelligent document processing solutions—capable of understanding and extracting data from any document.
This comprehensive demonstration of the Quality Analytics dashboard in ABBYY Vantage shows how you can track the chain of documents that are being processed without human intervention over time (straight-through processing rate). Key points include tracking document processing, optimizing human-in-the-loop resources, adjusting data verification settings, and analyzing extraction accuracy.
For many organizations, the question isn’t whether to invest in AI innovation, but when and how. In this article Ulf Persson, CEO of ABBYY, discusses the findings of our State of Intelligent Automation Report.
OCR solutions have come a long way, incorporating AI, machine learning, and natural language processing to deliver modern intelligent document processing solutions—capable of understanding and extracting data from any document.
This comprehensive demonstration of the Quality Analytics dashboard in ABBYY Vantage shows how you can track the chain of documents that are being processed without human intervention over time (straight-through processing rate). Key points include tracking document processing, optimizing human-in-the-loop resources, adjusting data verification settings, and analyzing extraction accuracy.
For many organizations, the question isn’t whether to invest in AI innovation, but when and how. In this article Ulf Persson, CEO of ABBYY, discusses the findings of our State of Intelligent Automation Report.
OCR solutions have come a long way, incorporating AI, machine learning, and natural language processing to deliver modern intelligent document processing solutions—capable of understanding and extracting data from any document.
This comprehensive demonstration of the Quality Analytics dashboard in ABBYY Vantage shows how you can track the chain of documents that are being processed without human intervention over time (straight-through processing rate). Key points include tracking document processing, optimizing human-in-the-loop resources, adjusting data verification settings, and analyzing extraction accuracy.
Some businesses are aiming to deploy AI agents for simple, repetitive tasks where a rules-based system would be faster and more efficient understand why and how in this article.
AI Ethics Evangelist Andrew Pery recommends organizations bridge the gap between innovation and compliance by adopting a layered approach to AI regulation that strikes a balance between innovation and potential adverse impacts.
By combining memory, AI models, and systems integration, AI agents push automation further than ever before, showcasing how far we’ve come—and how much further we can go.
