What You Get.

Production-ready infrastructure.

We'll build secure, scalable AI infrastructure that's ready for production from day one.

  • Security configuration and access controls
  • Request/response logging and audit capabilities
  • Automated scaling and cost monitoring
  • Optimised service selection (E.g. Bedrock, SageMaker, hybrid)

Data and model pipeline integration.

We'll deploy the data pipelines and knowledge systems your AI applications depend on.

  • Vector storage and search capabilities
  • Knowledge retrieval and augmentation patterns
  • Document processing and content workflows
  • Reliable model deployment and updates

AI operational excellence.

We'll set up the monitoring and operational tools you need to run AI reliably at scale.

  • Performance and monitoring dashboards
  • Cost tracking and budget management
  • Model quality assurance and testing
  • Business continuity and disaster recovery

How does it work?

Our team will build the operational foundation your AI and ML applications need to succeed in production, choosing the right combination and configuration of AWS services based on your requirements.

1

Design and planning workshop.

We'll review your requirements, validate technical designs, and create an implementation plan with clear milestones, timelines and success criteria.

2

Infrastructure implementation.

Our team will build your AI and ML foundations including security controls, key service configuration, knowledge base integration, and operational monitoring across your chosen AWS services.

3

Testing and handover.

We'll validate the implementation, provide documentation, and ensure your team understands how to operate and extend the platform for your AI and ML use cases.