Modern data foundations for AI: The strategic imperative for AI at scale
As organisations race to adopt generative and agentic AI, many are discovering a hard truth: AI ambition is only as strong as the data platforms that underpin it. Legacy SQL Server and Oracle environments were never designed to support the scale, integration, and velocity modern AI demands. This article explores why modern data foundations are now a strategic imperative for enabling AI at scale.
AWS Vector Store for RAG – Beyond OpenSearch
Compare AWS vector store options for RAG, including OpenSearch, S3 Vectors, Aurora pgvector, and more. This guide breaks down Bedrock Knowledge Bases integrations and custom pipeline approaches to help you choose the right solution based on latency, cost, and architecture.
On-Demand dbt Execution: Rethinking Analytics Engineering in Secure Cloud Environments
In secure enterprise cloud environments, traditional dbt deployment models can introduce unnecessary cost, security risk, and operational friction. This blog explores an on-demand, containerised dbt execution model that treats dbt as an ephemeral workload rather than a long-running service. Orchestrated with AWS MWAA and backed by ECS Fargate, the approach enables scalable, secure analytics transformations while improving cost efficiency, data quality observability, and CI/CD integration in modern enterprise data lakes.
Kafka ZooKeeper to KRaft: The Next Chapter in Apache Kafka (MSK and Kafka 3.9 Support)
Apache Kafka’s move from ZooKeeper to KRaft simplifies metadata management, boosts scalability, and accelerates failover. Learn how Kafka 3.9 on Amazon MSK leverages Raft consensus to streamline operations and support large-scale event streaming.
Continuous Evolution: Building Adaptability in the Age Of AI
In the age of AI, standing still is not an option. Continuous evolution and adaptability are essential for organisations to thrive, harness technology, and turn rapid change into a competitive advantage.
Measuring Agentic AI ROI: Introducing The Triad ROI Framework
Agentic AI is redefining how enterprises measure success — not just in innovation, but in real financial returns. In this second step toward Agentic AI excellence, we introduce the Triad ROI Framework, a practical model for quantifying value across cost savings, revenue growth, and risk reduction. Learn how to assess impact over time, track the right metrics, and build the foundations for sustainable AI-driven performance.
Agentic AI: From Hidden Tool to Trusted Partner
Agentic AI is transforming the way we work, evolving from hidden tools in the shadows to trusted collaborators. In this blog, we explore the four stages of agentic AI, the key risks of data, hallucination, and context drift, and why human-in-the-loop governance is essential for building trust and maximising productivity.
How AI Became My Coding Assistant (And Why It Should Be Yours Too)
AI coding assistants are changing how developers work. In this blog, Ian Ng shares how Amazon Q Developer became a powerful coding partner, helping automate routine tasks so developers can focus on architecture, problem-solving, and building better solutions faster.
5 Traits of a Winning Data Strategy for Business Success
A winning data strategy combines strong governance, reliable quality, and scalable architecture to drive measurable outcomes. With AWS and Cevo’s Data Strategy Diagnostic, organisations can build the foundation for AI-driven innovation and long-term growth.
AI Agent Evaluation Techniques: Step 1 in AI Excellence
Evaluating AI agents is the critical first step in achieving AI excellence. This blog explores modern frameworks and benchmarks that assess agents’ core capabilities, domain-specific performance, generalist reasoning, and evaluation methodologies, ensuring AI systems are reliable, adaptable, and ready to deliver real business value.