Cloud, data & AI platforms

Build the foundation your team can operate.

We design, build and migrate AWS platforms with the identity, data, telemetry, resilience and operating controls required for production AI—and the handover required for your team to own them.

What we build

Architecture through operational handover.

The work is designed for production constraints and for the people who will inherit the system after delivery.

Foundations01

Landing zones & platform architecture

Multi-account AWS environments with identity, network segmentation, guardrails, logging and deployment patterns designed from the first commit.

  • Infrastructure as code and delivery pipelines
  • Security, identity and workload boundaries
  • Architecture decisions and Well-Architected review
Data02

Data platforms & migrations

Lake and lakehouse architectures, ingestion, cataloguing, lineage, access control and staged migration of workloads and data estates.

  • Batch and streaming patterns
  • Data quality, lineage and ownership
  • Migration waves, rollback and cutover
AI workloads03

Production AI infrastructure

Serving, orchestration, evaluation and monitoring infrastructure for generative and predictive workloads, instrumented by use case.

  • Model and prompt versioning
  • Identity and event capture
  • Evaluation, guardrail and cost telemetry
Operations04

Observability, cost & resilience

Dashboards and alarms bound to runbooks, allocation and budget controls, and recovery objectives that are tested rather than assumed.

  • Service and control observability
  • FinOps and use-case cost attribution
  • Recovery rehearsal and incident readiness

Governed by design

The platform should produce the evidence governance requires.

Governance becomes operational when architecture exposes the signals needed to identify the actor, purpose, data, model, version, control decision and outcome for a material event.

IdentityWho or what invoked the system?
PurposeWhich authorised use was invoked?
DataWhat sources and classes were involved?
VersionWhich model, prompt, tool and policy applied?
DecisionWhat control outcome was reached?
EvidenceWhat must remain reviewable?

The handover is part of the build

A platform is not finished when the consultants can run it.

It is finished when the internal team can deploy, observe, recover and change it using the artefacts and operating model they own.

Exit acceptance test

  1. 01

    Deploy a complete environment through the delivery pipeline.

  2. 02

    Rollback a controlled change using the documented procedure.

  3. 03

    Respond to a rehearsed incident from alarms and runbooks.

  4. 04

    Explain the architecture and principal decisions without the delivery team.

Implementation lead

John Nathan

Co-founder · AI & data implementation lead

John is a cloud architect formerly of AWS Professional Services. He holds thirteen AWS certifications and the AWS Golden Jacket, and has architected and delivered production migrations and integrations for major banks, manufacturers and government bodies.

He has worked every side of an engagement, from writing the RFP through to handover, and builds for the team that will inherit the system.

13× AWS CertifiedAWS Golden JacketFormerly AWS Professional Services

Start with one real problem

Build the platform for the team that must own it.

Describe the workload, current estate, material constraints and the operating outcome required.

Discuss a platform