ABBYY Tech Terms
Definitions and terms about Process AI,
Document AI, and everything in between.
A
Agentic automation
An advanced form of AI-driven automation where systems not only complete tasks but also make autonomous decisions without human intervention. Unlike traditional automation, which follows set rules, agentic AI adapts to changing conditions and handles dynamic, unpredictable tasks.
AI OCR
Optical character recognition (OCR) that uses artificial intelligence (AI) and machine learning (ML) to improve text recognition, particularly in complex documents, poor-quality scans, or handwritten text. AI OCR uses machine learning and natural language processing to understand document structure and context.
Algorithmic fairness
A principle to ensure that AI decision-making is unbiased and equitable. This involves techniques to detect, reduce, and prevent bias in AI training data and algorithmic outcomes.
Artificial intelligence (AI)
Technology that simulates human cognitive functions like learning, reasoning, and decision-making. AI helps businesses run more efficiently by automating processes, improving data management, and enabling intelligent decision-making.
D
Deep machine learning (deepML)
A subset of machine learning (ML) that uses artificial neural networks to analyze vast amounts of data and improve predictions over time. Also known as deep learning, deepML can be pre-trained for specific tasks for accuracy right out of the box and continuous improvement.
Digital twin
A virtual version of a physical object, system, or process that updates in real time. It uses smart sensors to track performance, detect issues, and improve efficiency. In process simulation, digital twins let businesses test and refine workflows before making real-world changes.
Document skills
Pre-trained AI-powered extraction models that automate document-related tasks such as data extraction, classification, validation, and exception handling. Also called document models, these skills typically use ML, NLP, OCR, and other AI technologies to process documents with high accuracy and efficiency. Because document skills can be pre-trained, or trained by customers for a custom fit, businesses can quickly integrate them into workflows without extensive AI expertise.
E
Enterprise automation
The use of AI-driven technologies to improve business processes at scale. Enterprise automation allows businesses to reduce manual work, improve accuracy, and make workflows more efficient.
Enterprise content management (ECM)
A system that helps businesses store, organize, and manage digital content securely. ECM typically includes tools for content collaboration, workflow automation, and record-keeping.
Enterprise resource planning (ERP)
A system that integrates core business functions into a unified platform to improve data flow and decision-making across an organization.
Ethical AI
A framework for developing and using AI responsibly, ensuring fairness, transparency, accountability, and alignment with human values. Key aspects include algorithmic fairness, privacy protection, and explainable AI (XAI), all aimed at minimizing bias and promoting trustworthy AI systems.
Explainable AI (XAI)
AI systems designed to provide clear, interpretable explanations for their decisions, so users can understand why an AI model made a specific choice.
Extract, load, and transform (ELT)
A data integration process that extracts data from different sources then loads the raw data into a data warehouse or data lake for cleaning and organizing as needed. ELT takes advantage of cloud storage for faster, more flexible data handling and access.
Extract, transform, and load (ETL)
A data integration process that extracts data from different sources, cleans and organizes it, and then stores it in a database for analysis. ETL helps businesses turn raw data into useful insights for reporting and analytics.
F
Fast machine learning (FastML)
A lighter, more adaptive approach to ML that, even with minimal data, quickly fine-tunes AI models for improved accuracy.
G
Generative AI (genAI)
A type of AI that is trained to create new content, such as text, images, audio, video, and code, by learning from vast amounts of data. Instead of just analyzing and processing information, genAI generates new data based on probability and patterns it has learned.
H
Human-centric AI
AI designed with human values at its core. The goal of human-centric AI is to enhance user experience and support ethical decision-making that is in alignment with human and social needs.
Human-in-the-loop (HITL)
Also known as “manual verification,” HITL is a hybrid AI approach where humans step in to review, validate, or correct AI-driven processes when needed for quality control. Over time, AI learns from these interventions to improve accuracy.
Hyperautomation
The integration of multiple automation technologies, tools, and platforms to identify, evaluate, and automate as many business and IT processes as possible. Hyperautomation typically combines AI, RPA, IDP, process mining, and other automation solutions to reduce manual effort and improve efficiency.