MANAGED AI OPERATIONS

AI that ships is just the beginning.

Most AI projects fail after launch, not during build. Models drift. Accuracy degrades. Edge cases accumulate. MetaSys stays on after deployment to monitor performance, retrain models, respond to incidents, and keep your AI producing consistent outcomes over time.

Post-launch support|Ongoing retraining|SLA-backed

Why AI systems fail after launch.

Model drift

The world changes. Your training data does not. Over time, your AI starts making decisions based on outdated patterns and nobody notices until it is already causing damage.

No evaluation loop

Most builds ship without a feedback system. Without continuous evaluation, you have no way to know if your AI is getting better or getting worse week over week.

Unhandled edge cases

Production data is messier than training data. Edge cases that never appeared in testing show up constantly in the real world and bring your accuracy down.

No one owns post-launch

The team that built your AI moves on to the next project. You are left running a system nobody is watching and nobody is improving.

These are not rare problems. They happen to almost every AI deployment that ships without a managed operations layer. See systems we manage

WHAT WE COVER

Everything that keeps your AI performing.

Performance monitoring

We instrument your AI systems with evaluation pipelines that track accuracy, latency, output quality, and failure rates in real time. You get a live view of how your AI is performing and we get alerted before you do when something drops.

Real-time dashboards included

Model retraining and improvement

As new data flows through your system, we run retraining cycles on a scheduled or trigger-based cadence. Your model improves continuously instead of degrading slowly.

Scheduled or event-triggered retraining

Incident response

When your AI produces bad outputs, triggers errors, or hits edge cases it cannot handle, we respond within the terms of your SLA. We diagnose, patch, and restore normal operation with minimal disruption to your workflow.

SLA response times from 4 to 24 hours

Pipeline and infrastructure maintenance

Data pipelines break. APIs change. Upstream systems get updated. We manage the full stack that feeds your AI so you are not firefighting integration issues on top of everything else.

Full-stack ownership post-launch

Capability expansion

Your business evolves. Your AI should too. We scope and deliver new capabilities on top of your existing system so you are not starting from scratch every time you need something new.

Roadmap-driven AI development
HOW WE ENGAGE

Choose the level of coverage you need.

MONITOR

Performance Monitoring

For teams that built their own AI and need a dedicated operations layer watching it.

  • Real-time performance dashboards
  • Weekly accuracy and latency reports
  • Alert thresholds and escalation rules
  • Monthly evaluation report
  • Email and Slack incident notifications

Starting point for most clients

Get a quote
OPERATEMOST POPULAR

Full Managed Operations

For production AI systems that need ongoing care, retraining, and incident response.

  • Everything in Monitor
  • Scheduled model retraining
  • Incident response with SLA
  • Pipeline and infrastructure maintenance
  • Quarterly capability review
  • Named engineer assigned to your account
  • Priority support channel
  • Monthly improvement report
Talk to us
EXPAND

Operate and Grow

For organizations that want continuous AI improvement and new capability delivery on a roadmap.

  • Everything in Operate
  • Quarterly capability sprints
  • Roadmap planning and prioritization
  • Integration of new data sources
  • Strategic AI advisory

Best for enterprise and scaling orgs

Get a quote

All plans are scoped per engagement. Pricing depends on system complexity, data volume, and required SLA. Contact us for a custom quote.

IN PRACTICE

What we deliver every month.

Performance accuracy report vs baseline
Model drift analysis and recommendations
Incident log and resolution summary
Retraining run outcomes and delta metrics
Pipeline health and uptime summary
Next month roadmap and improvement priorities

MANAGED OPS REPORT - APRIL 2026

System: underwriter-agent-v3

Period: Apr 1 to Apr 30

Accuracy (this month):
94.8%+1.2% vs last
Avg latency:
310mswithin SLA
Incidents:
2both resolved
Retraining runs:
3scheduled
Pipeline uptime:
99.91%
New edge cases logged:
1412 addressed
Open items:
2in next sprint

Next action: Expand retrieval chunk size for
long-form document processing

WHO NEEDS THIS

You need managed AI operations if...

You have an AI system in production but no one is actively watching its performance
Your model accuracy was strong at launch but you have noticed output quality declining
Your data team built the AI but cannot take on ongoing operations work alongside new projects
You had an AI vendor build something and they handed it off with no post-launch support
You are in a regulated industry where AI decisions need to be auditable and explainable
You want to expand your AI capabilities over time but need someone to own the roadmap
BETTER TOGETHER

We build it and we operate it.

Most managed operations clients started as MetaSys build clients. When we build your AI system, we instrument it for observability from day one so the handoff to ongoing operations is seamless.

Need us to build first?

We design, build, and deploy production agentic AI systems, automation, and data platforms. Then we operate them.

See our AI capabilities

Already have a system?

Bring us an existing AI deployment and we will audit it, instrument it for monitoring, and take over operations within two weeks.

Talk to us
GET COVERAGE

Your AI should not be running unattended.

Talk to an AI operations engineer. We will audit your current deployment and tell you exactly what coverage you need.