Getting started with Cloud2 feels the same whether you’re a 25,000-employee enterprise or a specialized product team. Enterprise leaders don’t have the luxury of waiting months for AI experiments to pay off, which is why we focus on creating results fast, without compromising governance. At Cloud2, we help you put the foundation in place first: security, compliance, and guardrails that make generative AI safe at scale. With that foundation established, your business teams can innovate freely, IT retains full control, and value starts compounding from the very first use case. The outcome is predictable speed to value today, with a platform that continues to deliver tomorrow, whether you’re rolling out thousands of assistants or automating a single workflow. That’s how a global life-sciences leader Novo Nordisk opened self-service generative AI to the business. On Amazon Bedrock, employees can create and share assistants for real work, document drafting, retrieval, internal QA under tight security and cost controls. The scale is public: 2,500+ chatbots, 25,000 people using them, with a typical run-rate around $10/month per bot on serverless. Cloud2 worked with the customer to validate the architecture for security and scalability, so the platform could grow without chaos. Read more about Novo Nordisk use case. Take another example. With Grano’s EMMi DAM, we paired Bedrock with an event-driven pipeline: when a new asset lands, Lambda calls Bedrock (Nova models) to generate semantic tags and alt-text automatically, then writes metadata back to EMMi. No added clicks, better accessibility, cleaner search. One steady workflow improvement shipped safely, operated simply. Read more Grano EMMi -case What makes both projects feel the same from day one is the way we onboard. We begin inside your AWS environment with identity, policy, and data boundaries set first. We utilize AWS Bedrock as foundation and observability you’ll need later, prompt logging, latency and spend telemetry, unit economics you can show the CFO. Then we land the first production use case in your own workflow, not a demo lab. By the time the second and tenth team arrive, the environment and guardrails are already there. Enterprises choose this path because it balances speed with control. Model choice stays flexible; security stays boring (as it should); and costs stay predictable as adoption rises. Your people keep inventing, you keep owning the platform. If you want an enterprise-grade start that feels the same whether you’re rolling out 2,500 assistants or automating a single high-leverage workflow, let’s partner up: you bring the problem and data; AWS brings the primitives; Cloud2 brings the patterns, integrations, and operations to run it at scale. See the AWS case study for the global view, and our Grano write-up for the focused, everyday win. Ready when you are.
