Deep dive on AI Agents

Automate repetitive, low-value tasks with an intelligent agent to enhance efficiency and better address industry-specific challenges.

Evolution of Intelligent Systems: From Traditional Systems to AI Agents.

Type of Agentic Systems

Retrieval-Augmented Generation (RAG)

RAG grants generative artificial intelligence models information retrieval capabilities to make them able to include a specified set of documents and private data sources into its vast static training data.

Task-Specific
Agents

Agents are designed to address specific functions within a given domain. They serve as specialized modules that contribute to larger systems by efficiently managing discrete tasks.

Multi-Agent Systems (MAS)

Collection of autonomous agents that collaborate to solve interconnected problems. They coordinate tasks, providing scalability and adaptability in complex workflows. They may share a common memory or operate with isolated memories.

Human-Augmented Agents

Designed to collaborate with humans by automating complex tasks while incorporating human oversight, feedback, or decision-making. They enhance human capabilities as adaptive modules in larger systems.

 

Concrete examples of AI-Powered Digitalization