ABBYY Timeline

A collection of specialized AI skills, connectors, and pre-trained extraction models for various industries and document types to accelerate digital transformation and automation initiatives.

AI-powered process mining platform that delivers process discovery, analysis, monitoring, prediction, and simulation. Helps organizations understand workflows, identify bottlenecks, and optimize processes through automated digital twin creation.

Precise, reliable data extraction and validation from documents to power business decision-making, ensuring accuracy and quality of extracted information.

Document-specific AI models using CNNs, RNNs, and NLP that are pre-trained for document processing tasks, achieving up to 90% accuracy out of the box and over 95% when combined with fast ML. Requires 500-10,000 labeled documents for training.

API for integrating advanced text recognition and document processing capabilities into applications and automation workflows with minimal code.

Automatically sorts, divides, and organizes incoming documents using AI-powered classification and splitting capabilities.

Seamlessly capture any document from any source for processing in ABBYY's IDP platform.

Document-focused ML approach that works with minimal training data (1-2 documents per set) using clustering technology to group similar document layouts and train field extraction models per cluster, optimized for speed and low CPU consumption.

Measures the impact and business value of intelligent document processing programs, providing ROI and performance metrics.

Purpose-built AI document processing platform for efficient business process automation, including document input, OCR/ICR, classification, splitting, extraction, and validation across any document format and language.

Optical character recognition and handwriting/ICR technology for reliable, accurate text and handwriting extraction from documents, using CNNs, transformers, and language models based on ABBYY's 30+ years of OCR research.

A cutting-edge multimodal AI model that combines CNNs for image analysis with RoBERTa language model for text comprehension, offering zero-shot key/value pair extraction from documents without requiring extensive model training.

Pre-built analysis tools within ABBYY Timeline that enable detailed process understanding and insights for optimization opportunities.

Automatically builds an interactive digital twin of business processes based on actual event log data. Enables end-to-end process visualization to identify inefficiencies and bottlenecks.

Monitors processes in real-time to detect problems and enable actionable insights for process improvement and corrective action.

Advanced AI capability that predicts possible adverse outcomes in business processes, enabling proactive risk management and decision-making.

Uses historical process data to build a digital twin that allows organizations to simulate and evaluate potential process changes before implementation.

Data-driven insights and analytics to increase straight-through document processing rates and measure IDP quality and performance.

Connects external knowledge sources to LLMs to achieve greater accuracy and quality in GenAI outputs, providing AI-ready document data for context-grounded LLM responses.

Desktop recording and user interaction analysis capability that pinpoints repetitive or inefficient tasks by linking behavior data with process details.

A hybrid approach platform that combines Document AI and GenAI capabilities for intelligent document processing and automation.