AI & Agentic Solutions

Production AI and agents on AWS and Azure

Agentic AI & AI Agents

Build AI agents that act on your systems, with guardrails built in.

Generative AI on Amazon Bedrock

Secure generative AI applications inside your AWS environment.

AI Solutions on Microsoft Foundry

Enterprise AI on Microsoft Foundry and Azure OpenAI.

RAG & Enterprise Knowledge Assistants

Accurate, cited answers from your own documents and data.

AI Platform Foundations & LLMOps

Run AI in production with DevOps discipline.

Data & ML Platform Engineering

Design and build scalable data and ML platforms for analytics and AI workloads

Cloud Architecture & Data Platform Engineering

Design scalable cloud and data platforms that last

Cloud Platform Foundations

Establish secure, scalable cloud landing zones and core platform services

Cloud Strategy & Architecture Reviews

Assess cloud architectures to improve scalability, security, and cost efficiency

Cloud-Native Application Architecture

Design modern, resilient application architectures for cloud-native environments

Hybrid Cloud & Migration

Design, modernise, and operate hybrid and on-prem infrastructure

Hybrid Cloud & Migration

Enterprise-ready hybrid infrastructure, built for scale

DevOps, CI/CD & Infrastructure Automation

Automate infrastructure and delivery pipelines with confidence

DevOps, CI/CD & Infrastructure Automation

Automate delivery. Reduce risk. Scale with confidence.

Cloud Cost Optimisation & FinOps

Control cloud spend with clear visibility and governance

Cloud Cost Optimisation & FinOps

Engineering-led cost optimisation with real, measurable savings

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AI Platform Foundations & LLMOps

The cloud platform, pipelines and controls that let you run AI in production with the same discipline as the rest of your software.

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DevOps Discipline for AI.

Many AI projects stall between prototype and production. The gap is rarely the model; it is the platform around it. We apply our infrastructure and DevOps experience to AI: landing zones, model gateways, evaluation pipelines and observability, so every model, prompt and agent is versioned, tested and monitored.

What This Includes

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AI-ready landing zones: model access policies, GPU and throughput quotas, private endpoints

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Model gateways for routing, rate limiting and fallback across providers

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Prompt and model version management

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Automated evaluation pipelines in CI/CD

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Observability: tracing, latency, quality and token-cost dashboards

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MLOps for custom and fine-tuned models on Amazon SageMaker and Azure Machine Learning

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Governance: audit logs, data retention and responsible AI controls

How an Engagement Works

We assess your current platform and AI initiatives, then deliver a reference AI platform as code: landing zone, gateway, pipelines and dashboards. New AI use cases can then be built on a proven base instead of starting from scratch.

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Why Tech Teams Trust Us

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Leadership with 20+ years of infrastructure and DevOps delivery

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Everything as code: Terraform, CDK, Bicep and CI/CD

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Cost and security controls built in from the start

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Let’s Build Your AI Platform

Book a free discovery session to review your AI platform and the path from prototype to production.