Cognizant Enhances Neuro AI Platform with Multi-Agent Capabilities for Improved Enterprise AI Adoption

Cognizant Unveils Enhanced Neuro AI Platform

Cognizant, a leading information technology services company, has announced significant enhancements to its Neuro AI platform, aimed at accelerating enterprise adoption of artificial intelligence (AI) 1

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Key Features of the Enhanced Neuro AI Platform

The revamped Neuro AI platform offers several advanced features:

1. Multi-agent discovery tool: The "Opportunity Finder" helps businesses identify AI decisioning use cases through a guided approach 3

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2. Large Language Model (LLM) assistants: These AI-powered assistants facilitate various stages of the AI development process 3

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3. Model Orchestrator: A drag-and-drop tool that streamlines data preparation and application of machine learning models 3

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4. Synthetic data generation: The platform can generate synthetic data or work with anonymized data to create AI models 3

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5. Industry-specific configurations: Pre-configured templates cater to various sectors such as healthcare, finance, and agriculture 3

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Addressing Enterprise AI Challenges

The enhancements to Neuro AI address key challenges faced by enterprises in implementing and scaling AI solutions. According to a Cognizant and Oxford Economics study, 70% of enterprises feel they're not moving fast enough in leveraging AI for new revenue opportunities 3

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Babak Hodjat, Chief Technology Officer for AI at Cognizant, emphasized the platform's unique approach: "Multi-agent AI systems hold the key to solving these problems, which is why Neuro AI is now built with one at its core" 3

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The Four-Step AI Development Process

Neuro AI's development process consists of four main steps, each utilizing pre-configured agents:

1. Opportunity Finder: Deploys agents to search for industry-specific use cases.
2. Scoping Agent: Evaluates the use case's impact on specific categories and performance indicators.
3. Data Generator: Creates synthetic data related to the use case for testing.
4. Model Orchestrator: Sets up the application using multiple specialized agents 2

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Empowering Business Leaders

The platform is designed to put business leaders, not just data scientists, in control of AI development. It allows them to leverage their domain knowledge to quickly test and establish decision-making use cases for AI in minutes 3

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Technical Framework and Flexibility

Cognizant's team used LangChain as a framework to build out its multi-agent orchestration, ensuring the platform remains LLM-agnostic. This flexibility allows clients to use both open and closed models according to their preferences 2

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Competitive Landscape

As competition in AI application consulting grows, Cognizant's enhanced Neuro AI platform positions the company strongly in the market. Other major players like Accenture, McKinsey, and enterprise software providers such as Salesforce and SAP are also offering AI platforms and services to cater to the increasing demand for enterprise AI solutions 2

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