Skip to content
BlueOrbitAI
Cloud & DevOps

A system nobody operates decays within a quarter.

Models drift, providers deprecate, traffic grows and costs compound. We build the infrastructure and the operational discipline that keep an AI system accurate and affordable long after the launch announcement.
Talk to an expertSee our work

What’s included

  • Managed hosting
  • Cloud architecture
  • CI/CD
  • Evaluation pipelines
  • Cost control

Yours

the cloud account, the keys, the logs and the bill

Region

chosen before we build, not after a support ticket

Capabilities

What we deliver

Cloud architecture, managed hosting, CI/CD and MLOps that keep your products fast, secure and affordable as usage grows.

  • Cloud architecture

    AWS, Azure or GCP designed for your residency and audit requirements, hosted by us or in an account you own and can inspect.

  • On-premise and sovereign

    Open-weight models on your own hardware, with no external API calls, for data that must not leave the building.

  • CI/CD with quality gates

    Pipelines where an evaluation regression blocks the release, the same way a failing test does.

  • Monitoring and evaluation

    Quality, latency and cost tracked per release, with alerting on drift rather than discovery by complaint.

  • Model migrations

    Moving to a newer or cheaper model without a rebuild, verified against your own test set before the switch.

  • Cost and latency ceilings

    Hard limits per conversation, so an unusual week is a line on a chart rather than a conversation with finance.

Why it works

Still working in a year.

Launch is the cheap part. These four things are what decide whether the system is still accurate and affordable four quarters later.

Technologies we use

  • Terraform
  • Docker
  • GitHub Actions
  • Azure
  • AWS
  • vLLM
  • Grafana
Get a free consultation

  1. A release you can undo

    Every deployment has a rollback path, and every regression has a score that identified it before a user did.

  2. Residency as configuration

    You pick the region before we build. It is an architectural decision, not a support ticket afterwards.

  3. Costs that stay legible

    Per-conversation economics visible from week one, so the business case survives contact with real traffic.

  4. Hosted, operated, or handed over cleanly

    We host and run it, we operate it inside your own cloud account, or we leave you infrastructure as code and runbooks and walk away. Your choice, priced up front.

How a cloud engagement runs

  1. 01

    Assess

    We read the infrastructure as it is, and name the risks in writing.

  2. 02

    Design

    Architecture for your residency, audit and cost requirements.

  3. 03

    Build

    Infrastructure as code, pipelines with quality gates, monitoring from day one.

  4. 04

    Migrate

    A controlled cutover with a rollback path that has actually been tested.

  5. 05

    Operate

    Monthly evaluation, cost and latency reporting against the agreed ceilings.

Related case studies

All case studies

Cloud and DevOps: common questions

Straight answers to what we are asked most often.

Yes. We have delivered an on-premise retrieval assistant on open-weight models where zero bytes left the organisation's own infrastructure.

Yes. We can host it on infrastructure we manage, build and operate it inside your own cloud account, or install it on your own servers on premises. All three come with the same monitoring and release process, and the choice is usually settled by where your data is allowed to live.

Monitoring, evaluations on every release, cost and latency ceilings, model migrations, dependency and security updates, and an agreed on-call response.

Caching, smaller models for easy paths, streaming, and a hard ceiling per conversation. We report cost per conversation alongside quality, because the two trade against each other.

Explore related services