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Cognizant Launches Open-Source Neuro® AI Multi-Agent Accelerator

In a significant development for businesses across various industries, Cognizant (Nasdaq: CTSH) has announced the release of its Neuro® AI Multi-Agent Accelerator as open-source software. This new tool allows experts, researchers, and developers to prototype and construct multi-agent networks tailored to diverse use cases seamlessly.

Cognizant's initiative aims to propel the adoption of artificial intelligence by fostering collaboration in building and customizing multi-agent systems. This innovative software is expected to revolutionize adaptive operations and real-time decision-making processes within organizations. Cognizant’s Multi-Agent Services suite already allows companies to deploy extensive networks efficiently and manage them effectively in production settings.

A Market Poised for Growth

The market for intelligent agents is forecasted to experience rapid growth from $5.1 billion in 2024 to an estimated $47.1 billion by 2030. The launch of the open-source Neuro AI Multi-Agent Accelerator illustrates how businesses can leverage interconnected agents to unlock new revenue streams and enhance commercial value. The tool, developed by Cognizant’s AI lab, showcases the company's commitment to leading innovation in AI.

Prominent clients such as Telstra, Australia’s largest telecommunications and technology provider, are already collaborating with Cognizant to test and implement multi-agent systems. Kim Krogh Andersen, Senior Executive at Telstra, emphasized the value of this open-source tool in enabling their teams to rapidly prototype and integrate existing intelligent agents, which accelerates their software development cycle. They have already begun to witness improvements in quality, speed, and efficiency.

Success Stories in Diverse Industries

Cognizant has successfully assisted various organizations in integrating multi-agent systems. For instance, in the healthcare sector, the company helped create a Contract Negotiator network that expedited medical call processing times. Additionally, a consumer packaged goods firm leveraged the tool for analyzing supply chain management.

Currently, Cognizant is engaging in over 65 discussions with clients regarding agent-based AI solutions, showcasing the rising interest and corporate shift towards leveraging this technology.

Technical Features of the Accelerator

Setting up an effective multi-agent network requires orchestrating various agents, tools, and knowledge sources, including general-purpose large language models (LLMs) and organizational-specific systems like service-level management (SLM). The Neuro AI Multi-Agent Accelerator is designed to facilitate seamless integration with third-party APIs, RAG, and agents, including Salesforce’s Agentforce, Google’s Agentspace, and Crew AI.

Key Features Include:

• - Intelligent Opportunity Discovery: Users can input a company name or problem area, and the Agent Network Designer will propose a suitable agent network, enhancing the transition from idea to implementation.
• - Rapid Customization: Users can build and modify multi-agent systems utilizing natural language or predefined templates for areas like loan processing and customer service, significantly reducing development cycles and risks.
• - Scalable Distributed Operations: The tool's connectors support APIs and partner agents, enhancing operational efficiency while minimizing errors.
• - Private Data Security: The system isolates sensitive information through private data channels, ensuring regulatory compliance, particularly in finance and healthcare.
• - Cloud Provider Independence: Organizations can transition between open-source and commercial LLMs, along with different cloud providers, without requiring reconfiguration of their system.
• - Extensible, Coded Tools: Users can enhance their agent networks with custom-coded tools, which allow agents to base their decisions on real-time data.
• - Distributed Multi-Server Deployment: Agents can operate on multiple servers, facilitating scalable architectures.
• - Data-Driven Network Configuration: Users can define their systems purely via configuration files, ensuring rapid reuse across various projects.
• - Agent Testing Capabilities: The Agent Network Tester tool identifies bottlenecks or failures within the network, offering actionable insights into coordination issues and integration errors.

As part of its internal innovation, Cognizant has deployed the 1Cognizant assistant powered by the Neuro AI Accelerator. This tool consolidates and organizes multiple agents, providing immediate assistance to employees across various tasks, thereby increasing efficiency and breaking down internal silos.

Conclusion

Cognizant's commitment to pushing the boundaries of AI technology is evident through the open-source release of its Neuro AI Multi-Agent Accelerator, designed to empower businesses to innovate swiftly. By facilitating the rapid prototyping of multi-agent systems, Cognizant helps organizations stay ahead in an ever-evolving digital landscape. To learn more, visit Cognizant's website or follow them on social media.