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The key to operational AI: Modern data architecture

CIO

From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. To succeed, Operational AI requires a modern data architecture.

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Can serverless fix fintech’s scaling problem?

CIO

Add to this the escalating costs of maintaining legacy systems, which often act as bottlenecks for scalability. The latter option had emerged as a compelling solution, offering the promise of enhanced agility, reduced operational costs, and seamless scalability. Scalability. Architecture complexity. Legacy infrastructure.

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CIOs contend with gen AI growing pains

CIO

Unfortunately, despite hard-earned lessons around what works and what doesn’t, pressure-tested reference architectures for gen AI — what IT executives want most — remain few and far between, she said. As experts in financial services and commodity markets, there must be standard evaluation methods, he said.

Airlines 204
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Reimagine application modernisation with the power of generative AI

CIO

Alignment: Is the solution customisable for -specific architectures, and therefore able to unlock additional, unique efficiency, accuracy, and scalability improvements? The platform can automate up to 80% of code generation and transformation, as well as helping reduce time-to-market by 50%. [4]

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO

You pull an open-source large language model (LLM) to train on your corporate data so that the marketing team can build better assets, and the customer service team can provide customer-facing chatbots. Scalable data infrastructure As AI models become more complex, their computational requirements increase.

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Cloud modernization meets GenAI: new solutions expediate your efforts

CIO

Many legacy applications were not designed for flexibility and scalability. A faster time to market and a better customer experience GenAI copilots are well-established in the world of software engineering and will continue to proliferate and evolve. In this context, GenAI can be used to speed up release times.

Cloud 147
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AI in action: Stories of how enterprises are transforming and modernizing

CIO

AI practitioners and industry leaders discussed these trends, shared best practices, and provided real-world use cases during EXLs recent virtual event, AI in Action: Driving the Shift to Scalable AI. And its modular architecture distributes tasks across multiple agents in parallel, increasing the speed and scalability of migrations.