Cognizant Adds Multi-Agent Capabilities to Neuro AI

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Cognizant, a global IT services provider, has announced enhancements to its Neuro AI platform, designed to boost AI-driven productivity and business growth by leveraging multi-agent AI orchestration features. 

Neuro AI accelerates the adoption and integration of artificial intelligence within enterprises. According to Cognizant, the updated version allows users to create AI models using synthetic or anonymized data, ensuring privacy while delivering predictive insights for better decision-making. It also features industry-specific configurations, allowing businesses to scale AI applications more effectively.

A recent study by Cognizant and Oxford Economics reveals that although 77% of enterprises aim to use AI to generate new revenue opportunities, many face challenges in implementing and scaling AI use cases across their organizations. Only 26% have implemented cross-enterprise use cases. While the average AI investment planned for this year is $50 million, enterprises are cautious about scaling AI. 

Cognizant seeks to address this by offering an upgraded platform that integrates multi-agent AI orchestration, facilitating the enterprise AI productivity-to-growth journey. 

With the new platform, users can determine which challenges to prioritize and outline their scope. They have the option to upload anonymized data or create synthetic data to develop AI models. The platform aids in forecasting outcomes and offers recommendations for achieving specific business objectives. Additionally, it provides explanations for its output and assists in assessing the potential impact of various use cases.

Several new features have also been introduced, including the Opportunity Finder, a multi-agent discovery tool that identifies potential applications for AI decision-making. Once a use case is identified, the Scoping Agent evaluates its impact on various performance indicators.

The new Data Generator feature can be used to create synthetic data to test the application. Finally, the Model Orchestrator sets up the application by coordinating multiple agents to build the system.

The evolution of AI is entering a new phase with the rise of “Agentic AI,” a concept that signifies the potential for systems to operate autonomously, making intelligent decisions without human oversight. This is not just another industry buzzword – it could be a game-changer. Several companies and startups are showing strong interest in Agentic AI.

Vultr, a privately held cloud computing platform, today announced advanced serverless capabilities specifically for agentic AI, enabling scalable, flexible deployment of agentic technologies. Vultr aims to position this platform as an alternative to hyperscalers for autoscaling AI models and optimizing performance at the data center edge. 

Last week, Dovetail expanded its platform with Dovetail 3.0, which features agentic AI tools like “Ask Dovetail,” allowing users to interact with customer insights directly and get instant, actionable feedback. The company claims that this enhances how organizations understand and apply customer insights in decision-making and product development.

Agentic AI has applications in sales automation, cybersecurity, personalized marketing, IT management, and more. However, alongside its promise, challenges persist, including the propensity for LLMs to hallucinate and concerns regarding data privacy and security as these systems handle sensitive information.

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The rise of Agentic AI has paved the way for multi-agent systems, where collaborative intelligence can address complex tasks beyond the capabilities of individual agents. According to a Gartner study, this collective approach allows multiple agents to achieve common objectives, resulting in solutions that are more adaptable and scalable.

“Businesses are struggling with how and where to apply AI to solve business problems, and that’s why we’ve seen most AI use cases limited to prediction-based outcomes or single LLM chat-based solutions,” said Babak Hodjat, Chief Technology Officer of AI at Cognizant.

 “Multi-agent AI systems hold the key to solving these problems, which is why Cognizant Neuro AI is now built with one at its core. This platform puts business leaders – not just data scientists — in the driver’s seat, so they can tap into their own domain knowledge to quickly test and establish decision-making use cases for AI in minutes and then provide the resulting model code to iterate at scale.” 

Headquartered in New Jersey, Cognizant is actively investing in AI to enhance its offerings. Earlier this year, the company launched an AI Lab in San Francisco to accelerate the development of innovative AI solutions and drive digital transformation for its clients. 

Cognizant has also expanded its partnership with Google Cloud, Microsoft, Palo Alto Networks, and other key players in the industry to capitalize on the AI momentum and leverage the potential of Agentic technologies. 

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