Cloud-native agentic AI

Run autonomous workflows on AWS, Google Cloud, or Microsoft Azure with security, observability, and cost discipline baked in.

Cloud delivery is where agentic AI becomes operational: identities, secrets, telemetry, and change control matter as much as the model. We build on AWS, Google Cloud, and Microsoft Azure so your team can run, audit, and extend workflows — without surprise bills or unmaintainable glue code.

Strategy and workflow design sit alongside this service: see agentic AI consultancy for opportunity mapping and pilot delivery, and our Midlands SME playbook for adoption sequencing.

Why cloud-native matters for agents

Agents call tools and data repeatedly. That implies IAM-bound access, secret rotation, network boundaries, and logs you can query when something misbehaves. Lift-and-shift “AI in a VM” often misses those basics — we design for how agents actually run in production.

Typical build patterns

Secure orchestration and tool use

Least-privilege access to CRM, ticketing, databases, and internal APIs; structured error handling; idempotent actions where possible; clear escalation when confidence is low.

Evaluation and quality gates

Scoring outputs against golden sets, regression checks when prompts or models change, and human review queues for high-impact categories — so quality does not drift silently.

Cost and reliability

Caching and batching, right-sized runtimes, budgets and alerts, and separation of dev/stage/prod so experiments do not hit production data.

What you get

  • Reference architecture aligned to your cloud and compliance constraints
  • Implementation support for the integration and deployment path you choose
  • Handover artefacts: runbooks, monitoring hooks, and a path for continuous improvement

Plan a cloud architecture review