Cognizant’s Neuro AI: Revolutionizing Generative AI Applications with Multi-Agent Technology
Exciting times lie ahead in the world of artificial intelligence! Cognizant, a prominent player in tech consulting, has unveiled enhancements to its Neuro AI platform, which promises to empower businesses to create and test generative AI applications without needing extensive coding skills.
What’s New with Neuro AI?
Initially introduced last year, the Neuro AI platform is designed to encourage organizations to brainstorm, prototype, and refine AI applications at their own pace. Cognizant’s Chief Technology Officer for AI, Babak Hodjat, shared insights with VentureBeat on how the platform has evolved to allow enterprises to utilize it independently. “Clients expressed a desire to host and use this technology themselves, almost seeing it as a factory for generating ideas on harnessing generative AI," Hodjat explained.
A Unique Approach with Multi-Agent Capabilities
What sets the upgraded Neuro AI apart from other platforms is its sophisticated multi-agent functionality. This year has seen a surge in enterprises adopting AI agents, and Cognizant is leading the charge with its innovative design. The platform walks users through a four-step process, employing pre-configured agents that streamline application development:
- Opportunity Finder: Identify specific industry use cases.
- Scoping Agent: Evaluate the projected impact on key performance indicators.
- Data Generator: Create synthetic data for application testing.
- Model Orchestrator: Structure the final application using various interacting agents.
By initiating the process with user-defined challenges, the Opportunity Finder deploys agents to pinpoint relevant use cases. Following this, the Scoping Agent provides insights into the potential effects of implementing these use cases—essentially acting as a consultant throughout the journey.
Mastering Multi-Agent Communication
The brilliance of Neuro AI lies in its agents’ ability to communicate with one another to determine necessary capabilities. Hodjat elaborates, “Each agent encapsulates its expertise, allowing them to effectively collaborate. If one agent needs assistance with a use case, it can query another agent to get the support it requires.” This interconnectedness forms the foundation of Cognizant’s unique offering.
To maintain flexibility, the Neuro AI platform employs LangChain as its framework, ensuring it remains agnostic to different large language models (LLMs). Hodjat emphasized the importance of this adaptability, acknowledging that customers often prefer varied models for their projects.
The Competitive AI Landscape
Cognizant isn’t the only name making waves in the realm of generative AI. The landscape is intensifying, with many consulting firms carving niches in AI application consulting. Earlier this year, Cognizant opened an AI lab in San Francisco to further advance enterprise AI adoption. Competing firms like Accenture and McKinsey are also rolling out innovative solutions to help organizations navigate the complexities of AI technologies.
With platforms provided by giants like Salesforce, SAP, and Oracle, businesses are offered accessible tools for creating AI applications. Consulting firms are stepping in with tailored products to assist organizations that are still grappling with how to leverage generative AI effectively.
Conclusion
Cognizant’s Neuro AI platform is paving the way for organizations looking to explore the vast potential of generative AI without the traditional barriers like coding expertise. This evolution signifies a shift in how enterprises can harness AI to optimize their operations and drive innovation.
The AI Buzz Hub team is excited to see where these breakthroughs take us. Want to stay in the loop on all things AI? Subscribe to our newsletter or share this article with your fellow enthusiasts.
