Skip to main content Skip to footer
  • "com.cts.aem.core.models.NavigationItem@2c9ab520" Careers
  • "com.cts.aem.core.models.NavigationItem@31f62df5" News
  • "com.cts.aem.core.models.NavigationItem@230f66bb" Events
  • "com.cts.aem.core.models.NavigationItem@b6ae7da" Investors
Exploring Multi-agent AI Systems
Contact

What is a multi-agent AI system?

A multi-agent system is a network of AI agents that collaborate with each other and the user to support human decision-making. Each agent specializes in specific tasks, utilizing tools to exchange data and coordinate actions, streamlining operations and improving scalability across enterprises.

Among the key business benefits, multi-agent systems help break down enterprise silos by enabling AI agents across departments—such as HR, logistics, and procurement—to work together seamlessly. They automate end-to-end business processes, reduce inefficiencies, and drive faster, more informed decision-making.

How it works

At the core of each AI agent is a large language model (LLM) wrapped around a specialized app or function to handle natural language queries and analyze data. Agents interpret user requests, break them into subtasks and assign them to other specialized agents. They communicate continuously within the multi-agent framework, ensuring tasks are completed efficiently and effectively.

Know more

Multi- vs. Single-Agent AI Systems

As business needs grow more complex, the ability for agents to collaborate and adapt becomes essential. Explore how multi-agent systems build on the strengths of single agents.

 Multi-agent systemsSingle AI agent
CommunicationAgents share knowledge, collaborating to solve complex tasksAgent operates independently, focusing effectively on a single task
ScalabilityScale easily by updating agents without disrupting entire systemScaling typically requires retraining or redesigning the model
SpecializationAgents are optimized for specific tasks, improving performanceAgent is designed to handle diverse tasks, often prioritizing versatility
Operational flexibilityAgents can adapt and interact across various business operationsSingle agents are siloed helpers, not suitable across operations
Data handlingAgents handle data locally, improving efficiencyAgent is dependent on centralized data processing for insights
WHAT MULTI-AGENT AI DELIVERS

Key features and benefits

Multi-agent systems eliminate silos by enabling specialized agents to share insights, aligning staffing needs with logistical requirements across business functions.

Multi-agent systems improve user experience by enabling natural language queries, making complex systems intuitive and providing fast, personalized solutions.

Multi-agent systems are modular, allowing agents to be added, removed or updated without disruption, enabling effortless scaling and adaptation.

Agents log transaction intents, creating audit trails. Safeguard agents ensure ethical compliance and embed  security measures within each agent to secure sensitive data.

Multi-agent systems boost efficiency by assigning specialized tasks to agents, reducing redundancy and optimizing resource usage and system performance across operations.

Agentic AI Q&A

Stay informed with the most frequently asked questions about this groundbreaking technology.

Fundamentals
How can AI agents help my business?
How can AI agents help my business?

AI agents can automate tasks, increase efficiency and make real-time decisions.

A computer screen with multiple graphs and numbers
How does an AI agent differ from a chatbot?
How does an AI agent differ from a chatbot?

AI agents can perform intricate tasks based on context, whereas chatbots follow predefined scripts for basic user interactions.

A man working on a big computer screen
How do multi-agent systems differ from single agent systems?
How do multi-agent systems differ from single agent systems?

Multi-agent systems offer workflow orchestration, modularity, scalability and include built-in failover capabilities.

A man is looking at a computer screen with multiple graphs and numbers
Implementation
How do you ensure AI agents are aligned with business goals?
How do you ensure AI agents are aligned with business goals?

As business goals evolve, agents give you the flexibility to optimize your workflow to align with new KPIs.

A man holding a pen and touching a mobile screen
How do AI agents work as a team across the enterprise?
How do AI agents work as a team across the enterprise?

AI agents share data, coordinate tasks, and optimize decisions while ensuring security and compliance.

A man seeing a computer screen very closely
How do you design agent networks with governance built-in?
How do you design agent networks with governance built-in?

Include a responsible AI framework and oversight agents for auditability, explainability, and flagging of non-compliant outcomes for human review.

A man presenting a report to colleagues

Spotlight

Introducing Neuro AI Multi-Agent Accelerator and Cognizant Multi-Agent Services Suite

Discover how this no-code framework and suite enable businesses to rapidly prototype, customize and scale collaborative agent networks across their entire enterprise.

Know more
Babak Hodjat making a presentation at Discovery

Explore multi-agent AI in action

Take the first step in enabling multi-agent systems for your business

Learn more about scalable, agent-driven solutions that can empower your enterprise.