Strategy & Transformation

Graph AI: A New Silver Bullet from AI Vendors?

The generative AI (genAI) hype cycle is currently experiencing its trough of disillusionment, particularly in the application of retrieval augmented generation pipelines to enterprise applications. Despite numerous attempts, these systems have struggled to reduce hallucinations in output to levels acceptable for enterprise use. However, amidst this challenging period, a promising approach is emerging: the fusion of knowledge graphs into AI applications. Will it deliver?

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assurance

LLMOps Strategies and Frameworks for Enterprise Applications

DevOps. MLOps. LLMOps. Do IT teams need yet another buzzword? While it may be tempting to think of large language model ops (LLMOps) as a subset of machine learning ops (MLOps), that would prevent us from exploiting the real benefits of building enterprise applications with large language models (LLMs) – scale and speed of development.

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Where is Retrieval Augmented Generation (RAG) Going 5 Years from Now?

This paper outlines the key technological developments driving changes in retrieval augmented generation (RAG). Mapping those changes on a non-linear trajectory, we predict the near future, and provide actionable recommendations for organisations to stay ahead of the curve in the rapidly evolving landscape of enterprise artificial intelligence (AI).

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Modernising the Legacy Systems Portfolio

Legacy systems are typically challenging for CIOs – they often support critical business processes; they are expensive to replace and increasingly don’t meet business needs. As a result, they have been historically placed into the too hard basket. CIOs with significant legacy issues need to develop a deliberate strategy to address these challenges, rather than the squeaky wheel approach.

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