Executive Summary

Ethermind is an AI company building the next generation of knowledge management. Their platform delivers AI Knowledge Agents that help organisations keep their expertise in-house - capturing, retaining, and operationalising institutional knowledge so it stays accessible across the organisation.

The Opportunity

As Ethermind prepared to move their platform to AWS, the need for a robust, secure foundation was clear from the outset. Running AI Knowledge Agents at scale demands more than compute - it requires a governed cloud environment with repeatable delivery, layered security, and cost visibility from the start. The requirement was to design and implement a production-grade AWS environment, deploy the core platform components, and establish the operational foundations the team could build on confidently.

Our Approach

To give Ethermind a secure, scalable foundation for their AI platform, Several Clouds implemented the environment in a deliberate sequence - governance first, then platform, then delivery - so each layer built on a controlled baseline rather than retrofitting controls later.

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The foundation started with a multi-account AWS landing zone using Control Tower, separating environments with clear operational boundaries and consistent guardrails from day one. Centralised identity management and connectivity were put in place early, ensuring access was standardised and private from the outset.

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With the baseline established, the full application platform was delivered as infrastructure as code - containerised workloads running on Kubernetes, backed by managed database and caching layers, and served through a CDN-accelerated, WAF-protected public layer. A CI/CD pipeline connects every code change to a consistent, automated path to production.

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Security, observability, and cost management were built in throughout. Layered controls span identity, network, data, and continuous monitoring. Cloud spend is fully visible and governed in line with the FinOps framework. The engagement closed with solution documentation and knowledge transfer, leaving the team equipped to operate and extend the environment independently.

Results & Benefits

The outcome is a production-ready AWS environment that is secure, observable, and cost-aware - built on governed foundations and delivered in a short timeframe. Ethermind's AI Knowledge Agents are live in production and the team ships with confidence - on infrastructure that is auditable, reproducible, and straightforward to extend as the product and team grow. Ethermind's institutional knowledge platform now runs on a foundation built to scale with it.

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