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Data and AI Operations

Keep platforms, pipelines and models healthy, cost-effective and improving after go-live.

Most of the life of a data platform or AI model happens after launch. Pipelines break when sources change, models drift, AI costs grow with usage, and nobody owns the improvements.

We help organisations set up the practices, tooling and teams to operate data and AI as a service, or support them while internal teams build that capability.

What is included

Service offerings

09.1

MLOps and LLMOps

Deployment, versioning, monitoring and retraining for ML and LLM systems.

  • MLOps platform
  • Model registry and monitoring
  • Retraining process

09.2

Data platform operations

Monitoring, incident handling and change management for data platforms.

  • Runbooks
  • Monitoring and alerting
  • Service levels

09.3

AI cost management

Track and optimise model, token and compute costs per use case.

  • Cost per use case
  • Routing and caching options
  • Optimisation plan

09.4

Observability

Freshness, quality, performance and usage visible in one place.

  • Observability stack
  • Dashboards
  • Alert rules

09.5

Capability transfer

Train and coach internal teams to run the platforms themselves.

  • Operating model
  • Training plan
  • Handover

When to call us

Signs you need this

  • Models in production with no monitoring.
  • Generative AI costs rising without visibility.
  • Data incidents discovered by business users.
  • A delivery partner is leaving and knowledge must stay.

Approach

How we work

  1. 01Stabilise

    Monitoring, runbooks and incident handling for what is live.

  2. 02Standardise

    Common deployment, testing and release practices.

  3. 03Optimise

    Reduce cost and improve performance and reliability.

  4. 04Transfer

    Build internal capability and hand over.

Standards and frameworks

Aligned with recognised practice

  • MLOps and LLMOps practices
  • Site reliability engineering (SRE)
  • ITIL 4 service management

Solutions

Where this service is applied

Data foundations

Modern Data Platforms

One governed platform for analytics and AI, designed for your scale and your region.

View solution Decision intelligence

Predictive Analytics

Forecasts and risk scores that are trusted enough to act on.

View solution Applied AI

Enterprise AI Assistants

Secure assistants that know your business and act within your rules.

View solution Data foundations

Data Quality and Governance Systems

Governance that runs in the systems, not in the slide deck.

View solution

Technology

Platforms we work with

Vendor-neutral: examples of platforms commonly used in this service. Names identify technologies only and do not imply a partnership.

  • MLflow
  • Datadog
  • Grafana
  • Prometheus
  • OpenTelemetry
  • Monte Carlo
  • Kubernetes
  • GitHub
See the full technology ecosystem →

Insights

Further reading

The Real Cost of GenAI in Production

Token prices are the most visible line in a generative AI budget and rarely the decisive one. Production cost is set by architecture, by the people around the model and, if you self-host, by utilization.

Read →

The Enterprise LLM Landscape 2026

At the frontier, the best model changes with the month, the referee and the effort setting. Price and deployment route differ by orders of magnitude. Choose the route and build the evaluation capability; treat the model as a replaceable part.

Read →

Kubernetes for Data and AI

Kubernetes has become the default substrate for AI inference, but it is an operating model, not a product. Adopt it when you can staff a platform team and have enough workloads to share it; otherwise, buy the managed service and keep your containers portable.

Read →

Databricks for Pipelines, ML and LLMs

Databricks' real strength is that pipelines, models, agents and their traces share one governance layer. The price is that its newest AI features are serverless, billed on separate lines and unevenly available by region. Adopt it workload by workload, not wholesale.

Read →

Talk to us about Data and AI Operations

Engage this service on its own or as part of a solution. We will agree scope, outcomes and the right team with you.

Start a conversation

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AI Strategy and Solutions

From AI ambition to a portfolio of use cases that reach production and pay back.

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