Reimagining Developer Productivity with AWS GenAI-Powered Platforms


About the customer

Developer Productivity and Experience

S&P Global’s engineering teams grappled with a fragmented developer experience. Constantly switching between tools, repositories, and integrations meant developers spent more time on repetitive tasks and less on innovation. This context-switching drained productivity, making it harder for teams to deliver at the speed the business demanded.

Standardization and Infrastructure Agility

The lack of reusable assets and consistent environments led to duplication of effort, with teams often rebuilding similar components from scratch. Coupled with inefficient access to infrastructure, APIs, and templates, scaling applications became a slow, error-prone process. Without centralized access to infrastructure-as-code (IaC) and delivery frameworks, agility was compromised, delaying time-to-market and inflating costs.

Accountability, Security, and Governance

Leadership lacked granular visibility into project-level engineering costs, limiting their ability to measure ROI and enforce financial discipline. At the same time, as AI adoption grew, embedding compliance, explainability, and observability into workflows became a critical need. Security and governance gaps risked undermining trust, highlighting the urgency of stronger guardrails for responsible innovation

Smarter Developer Experience


Accelerated Discovery & Reuse

Trust, Visibility & Accountability


Consistency and Productivity at Scale

By standardizing the developer experience, S&P Global eliminated context switching and reduced onboarding friction. Centralized assets and consistent workflows created a uniform environment for teams, minimizing learning curve gaps and enabling developers to focus on innovation rather than repetitive setup. This consistency not only boosted productivity but also accelerated time-to-value for new projects.

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Trusted, Enterprise-Grade AWS GenAI Adoption

The platform embedded explainability, observability, and cost accountability into every stage of development. This gave teams the confidence to scale GenAI safely in production, ensuring innovation was always balanced with compliance and financial discipline. By integrating trust and transparency directly into the workflows, S&P Global could embrace AI at scale without compromising governance or accountability.

Efficiency and Engagement That Lasts

Pre-approved IaC and APIs streamlined the idea-to-production cycle, reducing delays and removing integration hurdles. Teams shipped faster, without the burden of repetitive tasks. At the same time, weekly dashboards showcasing adoption metrics and usage insights encouraged healthy competition among developers. This visibility not only sustained engagement but also drove long-term platform adoption across the enterprise.

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