About
Cognitive Automation
Cognitive Automation extends RPA by adding intelligence such as NLP, OCR, computer vision, and decision models. It automates semi-structured or unstructured workflows by understanding context, extracting meaning, and making decisions. This dramatically increases the scope and complexity of processes that can be automated.
Key Features
Natural Language Processing & Understanding
Enables automation of text-heavy workflows like emails, documents, and customer interactions. Understands context, sentiment, and intent for smarter decisions.
01
Document Processing with OCR & Vision Models
Extracts data from forms, invoices, and images with high accuracy using intelligent document recognition. Converts unstructured content into actionable structured data.
02
AI-Driven Decision Engines
Applies business rules and machine learning to assess scenarios and choose optimal actions. Supports advanced process flows involving judgment-based decisions.
03
Why does
Key Objectives of Cognitive Automation
Automate Complex, Knowledge-Based Workflows
Expand automation beyond simple tasks to processes involving interpretation, reasoning, and contextual understanding. Reduce reliance on human review.
Enhance Data Extraction & Information Quality
Improve precision in document handling and data ingestion for downstream systems. Enable end-to-end processing of diverse document types.
Boost Efficiency in Content-Heavy Operations
Accelerate workflows across finance, HR, customer service, and compliance by reducing manual data reading, verification, and interpretation.
MNS
Case Studies From Challenge to Change
United States Patent and Trademark Office (USPTO)
Network Analysis
The New York State Office of Information Technology Services
Hosting Solution
City Of Dallas, TX
Data Recovery