Cloudnaut is an AWS specialist consulting firm. We work backwards from the outcome your customer needs, engineer it to production standards, and remain accountable after go-live.
We concentrate on a single platform. That decision defines the depth of our capability and the commitments we are able to make.
One platform / Six commitmentsOur engineers work on AWS daily, across every service we deploy for clients.
Every engagement begins with the experience your customer should have, and reasons back to the architecture.
The team that designs your solution delivers it and answers for the result.
Where the evidence contradicts the plan, we say so while the decision can still change.
Testing, documentation and security review form our definition of done from the first commit.
We support the system after go-live and train your engineers to operate it independently.
We begin with the experience your customer should have and the measures that prove it was delivered. Your leadership agrees a single documented outcome before design begins.
An illustrative outcome: one statement that the architecture, data and model layers must deliver.
Agree the measures, the baseline, and the conditions for stopping.
Evaluate the result against the baseline, per business process.
The team that agrees the outcome delivers it, end to end.
The people who design your solution build it. You work with one team from the first workshop to production, accountable throughout.
The design you approve is the system you get.
Establish the current state, define the target state, then build and transition to your team.
We document the systems you operate today, the condition of your data, your security posture, and the cost of the problems in scope. The result is an agreed baseline for the programme.
We define the target state, working backwards from the experience your customer should have. Your leadership agrees a single objective and the measures that will determine whether it has been met.
We build and deploy on AWS to production standards, then support the system through an agreed stabilisation period while training your engineers to operate it. We hand over a working system and the capability to run it.
Delivered into production on AWS, backed by reusable assets and reference architectures.
Task-completing agents on Amazon Bedrock AgentCore, with session-isolated compute, policy evaluation on every tool call, and a complete audit trail.
Managed foundation model access on Bedrock, customised where the return justifies it and benchmarked against a conventional machine learning baseline.
S3 table buckets in open Iceberg format, catalogued in Glue, with cell-level permissions enforced consistently across every query engine.
Streaming ingestion landed, transformed and made queryable in the lakehouse, so analysis reflects the current state of the business.
Forecasting, churn, pricing and anomaly detection, where conventional models outperform language models. SageMaker from training through deployment, with drift monitoring and automated retraining.
Dashboards built on the measures your teams manage against, served from the governed lake, alongside the retrieval endpoints your models and agents consume.
Contact centre platforms migrated from legacy estates with continuity of service, then extended with conversational AI that resolves customer intent.
Auditable engineering velocity: Kiro specifications and steering, AI-assisted refactoring, and governance measured against a pre-implementation baseline.
Evidence-based improvement: OpenTelemetry traces inform evaluation, evaluation drives prompt and tool changes, and controlled testing validates each change before release.
Advanced Tier recognises validated delivery capability: certified engineers and customer deployments verified by AWS.
Attested operating practices.
Certified information security management.
Stabilisation, capability transfer, and a working system your team can run.
Tell us what your customer should be able to do that they cannot today. We will work backwards from there.
