Insights
Practical Lessons from Deploying MCP in the Enterprise
Practical learnings from real enterprise deployments of MCP: architecture decisions, challenges, tradeoffs and guidelines for adoption at scale.
AWS Summit London 2025: What to watch?
A guide for AI-interested attendees: key sessions and topics around AI and data and how WeBuild‑AI will be involved in AWS Summit London 2025.
Unlocking AI's Potential: The C-Suite Blueprint for Responsible Innovation
A C‑level framework to adopting AI responsibly, balancing innovation with risk, oversight and scalability to achieve fast and ethically scale solutions.
How We Built An AI Launchpad in Under 20 Days on Amazon Web Services
Co-founder of WeBuild-AI, Mark Simpson, shares how WeBuild‑AI built our “Pathway” launchpad using AWS and generative AI, completing over 200 deployments in 20 days to validate our product architecture.
Key Safety Features for Creating AI-Enabled Products with Amazon Bedrock
Explore Amazon Bedrock's essential safety features for responsible AI deployment. Learn how guardrails like content filters, denied topics, and contextual grounding checks mitigate risks in AI-enabled products. Discover how these features prevent incidents like chatbot jailbreaking and misinformation, ensuring compliance and protecting brand reputation. Ideal for technology decision-makers seeking to innovate with AI while prioritising safety and ethics in an era of increasing AI capabilities and public scrutiny.
AI Ethics & MLOps - Go Fast, Without Breaking Transparency
Explore how MLOps can ensure AI ethics and transparency in your organisation in "AI Ethics & MLOps - Go Fast, Without Breaking Transparency." This blog by Ben Saunders delves into the importance of integrating ethical considerations and governance into the machine learning lifecycle. Learn how MLOps frameworks can help build, deploy, and manage AI models that are reliable, transparent, and compliant with legal standards, fostering trust among customers and regulators while accelerating AI adoption.
What is a Digital Twin and what capabilities do you need to build one for your business?
Discover how digital twins are revolutionising data-driven decision-making for enterprise organisations in this comprehensive blog. Learn how digital twins—virtual replicas of physical systems—enhance operational efficiency, optimise performance, and improve customer experiences across industries. Explore key capabilities needed to build effective digital twins, from data acquisition to continuous improvement, and uncover real-world examples from leading companies like Rolls-Royce and BP. This guide provides actionable insights for organizations looking to leverage digital twins for competitive advantage and growth in a fast-paced business environment.
LLMOps on AWS: Mastering Large Language Model Operations with Amazon Bedrock
Explore how to operationalise LLMs using AWS tools, with best practices for scalability, observability and secure deployment.
50+ Key Questions to Build Your AI Strategy Around
Develop an effective AI strategy with WeBuild-AI. Our comprehensive guide covers essential questions to align AI initiatives with your business goals, ensuring ethical, data-driven, and impactful outcomes. Learn how to navigate AI implementation, optimise data management, identify key use cases, and foster innovation within your organisation.