Claude services · Managed AI Operations
Your Claude workloads run in production to an agreed SLA.
We monitor availability, latency, errors, quality, and spend, respond to incidents to agreed targets, run the regression suite so quality drift is caught, manage prompt and model changes, and report monthly.
- Engagement
- Scoped monthly fee
- Ongoing programme
- Typical timeframe
- Ongoing, monthly, 12-month initial term
- Who it's for
- Organisations with Claude workloads in production and no team whose job it is to keep them healthy.
- What you walk away with
- Production Claude workloads run to an SLA, with quality and cost held inside agreed bounds.
What you get
What we deliver.
- Service design and onboarding: scope, SLAs, escalation paths, and runbooks
- Monitoring and alerting on availability, latency, error rates, quality, and spend
- Incident response to agreed response and resolution targets
- Ongoing evaluation so quality drift is caught by a regression suite, not by a customer
- Change management for prompts, models, and tools: versioned, tested, and released
- Model and version upgrades assessed and rolled out without regressions
- Capacity, rate-limit, and cost management inside an agreed envelope
- Monthly service reporting and a quarterly service review
In practice
- 01A customer-facing AI feature that needs 24/7 accountability
- 02Internal agents whose quality drifted after a model upgrade nobody tested
- 03A team that built something good and has nobody to run it
Scope
What you need, and what is not included.
What you'll need
- Claude workloads in or near production
- Access to the environments, repositories, and observability we need to operate them
- A named service owner on your side
Not included
- Anthropic consumption and infrastructure costs (billed to you, managed by us)
- New feature or workload development (scoped as build engagements)
- Operation of systems outside the agreed Claude workload scope
12-month initial term, then month-to-month. SLAs, severity definitions, and cost envelope are agreed during service design.
The engagement
- 01Step 1
Service onboarding: discovery, runbooks, monitoring, and SLA agreement
- 02Step 2
Steady-state operation: monitoring, incident response, and change management
- 03Step 3
Continuous evaluation and improvement against quality and cost targets
- 04Step 4
Monthly reporting and quarterly service review with your owner
- An Anthropic Select Partner with Claude-certified architects. The people who scope your programme are the people who build it.
- 50+ specialists across strategy, implementation, automation, data, and custom development, so the Claude work is connected to the systems you run.
- Every engagement ends with training and documentation, so your team runs it without us.
Questions
Frequently asked questions.
What SLAs do you offer?
Response and resolution targets by severity, plus availability and quality targets on the workload itself. The numbers are set during service design to match the workload. An internal drafting assistant and a customer-facing capability carry different SLAs and different prices.
Do you have to have built the workload?
No. We onboard workloads built by your team or a third party. Onboarding includes a review, and we tell you what has to change before we can commit to an SLA.
How is consumption handled?
Anthropic bills you directly on your own account. We manage the spend against an agreed envelope, alert you before you approach it, and report on it monthly.
How is this priced?
Each engagement is scoped to your environment, seat count, systems in scope, and how much of the work you want to own internally. After a discovery call you get a fixed-fee proposal with defined deliverables.
Next step
Book a discovery call.
Tell us where you are with Claude and what you want from Managed AI Operations. You leave the call knowing whether it fits and what the fixed-fee proposal will cover.
30 minutes. No commitment.