Managed AI operations: LLMOps and AgentOps, run 24/7

AXIOMIO runs generative AI applications and agents in production as a managed service. Managed AI operations (LLMOps and AgentOps) covers 24/7 monitoring and tracing, evaluations on every change, guardrail management, model upgrades, AI security monitoring and testing, and token cost control. It is delivered by the same AWS MSP and Level 1 MSSP team that runs your AWS, for systems we built or systems built by someone else.

Frequently asked questions

What are managed AI services?

Managed AI services means a provider runs your AI applications and agents in production for you: monitoring, evaluations, guardrails, model upgrades, security, incident response and cost control, under agreed targets. It is to AI what managed services are to cloud infrastructure.

What is LLMOps, and how is it different from MLOps?

MLOps manages models you train: data pipelines, training, deployment and drift. LLMOps manages applications built on large language models you usually do not train: prompts, retrieval, guardrails, evaluations, model versions, token cost and agent behaviour. AgentOps adds tool permissions, step limits and tracing for agents.

Can you run AI systems that another team or vendor built?

Yes. We start with a review of the architecture, data flows, security and cost, build an evaluation set and add tracing where it is missing, then take over operations with a transition plan. Anything we find that blocks safe operation is listed and quoted before we take responsibility.

How do you control Amazon Bedrock and LLM token costs?

We measure cost per request and per task, set budgets and anomaly alerts, route simple requests to smaller models, cache repeated context, trim prompts and limit agent steps. Cost is reported monthly by application and team, alongside quality so savings never quietly cost accuracy.

How do you secure generative AI workloads?

We test applications and agents against the OWASP Top 10 for LLM Applications and the OWASP agentic risks, including prompt injection, sensitive data disclosure and tool misuse. In production, guardrails filter inputs and outputs, agents run with least-privilege identities, and AI events flow into the security monitoring we run as an AWS Level 1 MSSP.

Do you monitor model quality and drift?

Yes. Evaluation sets run before every change, and samples of live traffic are scored continuously for groundedness, task success and safety. When scores move outside the agreed range we investigate, roll back if needed and report the cause.

Does this replace our AWS managed service?

No, it extends it. If we already run your AWS, the AI workloads join the same SLA, team, Xops360 console and monthly review. If we do not, managed AI operations can be taken on its own.