Cognizant Reimagines its Neuro AI Platform to Bring GenAI to Life Faster, at Scale

Cognizant, the company engineering modern business, has enhanced its Cognizant Neuro AI platform to more rapidly and effectively derive value from generative AI (GenAI) use cases. While many enterprises still struggle to apply AI to solve business problems, the latest iteration of Cognizant Neuro AI allows business leaders—not just data scientists and engineering teams—to create an AI model that directly addresses their unique proprietary challenges.

Cognizant’s reimagined platform is a direct result of the way the AI surge is prompting many organizations to cash-in—but find these costly efforts unsuccessful. Citing a study by Cognizant and Oxford Economics, 76% of enterprises are seeking to adopt AI to drive new revenue opportunities yet are challenged by implementation and scaling roadblocks. In addition, 70% of enterprises feel that their pace of innovation is too slow.

By guiding business leaders through the processes of identifying their business use case, creating an AI model, and detailing how that use case will meet business objectives, Cognizant Neuro AI “bring[s] generative AI use strategies to life for enterprises—faster, more securely, and at scale—within minutes,” explained Babak Hodjat, CTO of AI at Cognizant.

This is accomplished by a powerful multi-agent discovery tool—dubbed Opportunity Finder—that interacts with users to identify potential AI decisioning use cases unique to their business.

As a large language model (LLM) assistant, Opportunity Finder “pull[s] from their world knowledge and publicly available data about the topic, and through a natural language dialog, formulate[s] several use-case outlines, reason[s] about the ROI…then move[s] on to draw up the details of the scope and even generate[s] a synthetic dataset to try the end system on,” said Hodjat. “Finally, a team [of] agents work autonomously to design and implement an end-to-end agent-based decision augmentation system based on the detailed scope and synthetic data generated earlier in the agentic pipeline.”

With Neuro AI’s Model Orchestrator, users are then able to organize and refine data, as well as apply machine learning (ML) models—including those that deal with outcome predictions and uncertainty modeling and explainability—through an intuitive, drag-and-drop interface. Centering simplicity, enterprises can iterate, test, and refine their AI models and strategies faster, without needing deep technical expertise, according to Cognizant.

Cognizant Neuro AI is designed to address a variety of use cases from the start with pre-built configurations for an assortment of verticals, including healthcare, finance, and agriculture, as well as offering general templates for supply chain, call center, customer retention, and price optimization.

“We’re most excited about the ability to use Cognizant Neuro AI to build use cases that can be rapidly scaled for businesses across any industry,” noted Hodjat. “[These updates] allow companies to not only build AI use cases that meet their business objectives but also pinpoint the right business challenges to solve in the first place.”

To learn more about Cognizant Neuro AI, please visit https://www.cognizant.com/us/en.