Who we are
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.
How we're different
We concentrate on a single platform. That decision defines the depth of our capability and the commitments we are able to make.
Working backwards
We begin with the experience your customer should have and the measures that would prove it was delivered. The architecture follows from that definition.
This discipline determines what gets built. Your leadership agrees a single documented outcome before design work begins, which is where misaligned programmes are identified and corrected.
One statement, agreed before design begins. The architecture, the data layer and the model layer all exist to deliver it, and are measured against it.
How we engage
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.
Our engagement model
Three phases: 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.
Our capabilities
Each is a capability we have delivered into production, with the reusable assets and reference architectures to support it.
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.
Guardrails
S3 table buckets in open Iceberg format, catalogued in Glue, with cell-level permissions enforced consistently across every query engine.
Iceberg
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.
Contact Lens
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.
Our partnership
Independently verified credentials, and a partnership that gives our engineers early visibility of the platform roadmap.
Advanced Tier is awarded on validated delivery capability: certified engineers and customer deployments verified by AWS. Concentrating on a single platform is what lets us commit to production standards.
Next step
Tell us what your customer should be able to do that they cannot today. We will work backwards from there.
