Month six is where AI projects quietly die.
Not with an outage. With drift — an API that changed, a policy nobody re-indexed, an accuracy drop small enough that people started double-checking the output, then stopped using it. Every CloudArk build ships assuming all three will happen, because they do.
| Items processed | 14,208 |
| Auto-resolved | 11,795 |
| Sent to human review | 2,413 |
| Accuracy vs. baseline | +0.4% |
| Incidents (P1 / P2) | 0 / 1 |
| Model spend vs. last month | -11% |
• Migrate 2 tasks to cheaper model
Long-term operational governance for live systems.
Anyone who has already been burned by a pilot
It worked in the demo, ran for a quarter, and quietly stopped being trusted.
Teams without an AI engineer on staff
And no intention of hiring one to babysit three workflows.
Businesses inheriting someone else's build
Including systems we didn't build. We'll assess it and tell you honestly whether it's maintainable.
SYSTEMS WE MONITOR
What's included.
Proactive monitoring, telemetry audits, and continuous model tuning to protect production uptime.
Pipeline health monitoring
Automated checks on every workflow with alerting before you notice a problem, not after a customer does.
- Automated checks per workflow
- Alerting before user impact
- Public status page
Weekly output regression checks
Sample outputs re-scored against expected results, so accuracy drift is caught as a trend rather than a complaint.
- Sampled output re-scoring
- Drift tracked as a trend
- Threshold-based alerts
API deprecation watch
We track the vendors you're integrated with and patch ahead of breaking changes rather than after them.
- Vendor changelog monitoring
- Patched ahead of breaking changes
- Staging verification first
Knowledge base refresh
Policy and document updates re-indexed on your schedule, so the system stops citing material you retired.
- Scheduled document re-indexing
- Retired content removed
- Citation accuracy verified
Model and cost review
Routing work to cheaper models where quality allows, reported monthly with the numbers shown.
- Per-task model routing
- Cheaper models where quality allows
- Monthly spend reporting
Response commitments.
Committed response times, in writing.
| Severity | Definition | First Response | Target Resolution |
|---|---|---|---|
| P1 — Down | A production pipeline has stopped or is producing wrong output | 1 business hour | Same business day |
| P2 — Degraded | Running, but with errors, delays, or an accuracy drop | 4 business hours | 2 business days |
| P3 — Change | Prompt, rule, or integration change request | 1 business day | 5 business days |
| P4 — Enhancement | New capability or workflow addition | 2 business days | Next build cycle |
How you reach us.
Shared Slack channel
Your team and your named engineer in one place. No ticket forms, no portal login. Most issues close here.
Email and ticket log
Everything raised is logged and trackable, wherever it started.
Live status page
Pipeline health, last run, and any active incident, visible without asking anyone.
Monthly review call
Thirty minutes with your engineer. What ran, what broke, what to build next.
How onboarding works.
From initial system telemetry baseline to quarterly continuous improvement roadmaps.
1. System review
Free. We assess what's running, how it's built, and what it would take to support. This applies to systems we didn't build too.
2. Baseline
Current accuracy, volume, and cost recorded, so improvement is measurable rather than asserted.
3. Instrumentation
Week one. Monitoring, alerting, and the status page go live before anything else changes.
4. Steady state
Monitoring, monthly reporting, and your included pool of change hours.
5. Roadmap
Quarterly. What's working, what should be retired, and what's worth building next.
Reference build. This is a standard implementation pattern for this problem, not a client project. It describes how CloudArk builds this kind of system and what delivery involves.
Knowledge Assistant Recovery & Governance
A knowledge assistant built by a previous vendor was still running but no longer trusted — the document set hadn't been re-indexed in eight months and staff had gone back to searching manually.
Built instrumentation and accuracy baselining, a scheduled re-indexing pipeline, a regression test set, and monthly reporting.
Figures are modelled to illustrate the shape of the change, not measured client results.
Both run on the same response commitments.
Managed AI
Monitoring, retuning, and cost control for live AI workflows.
Website care plans
Updates, backups, security patching, uptime monitoring, and content changes for sites we build or inherit.
Frequently asked questions.
Protect the long-term ROI of your AI systems.
Book a free system assessment to evaluate your current builds, telemetry, and ongoing support requirements.
- Practical business conversation with an engineer, not a sales deck.
- Clear architecture assessment and support SLA scope.
- You keep the audit findings whether we work together or not.
Thanks for reaching out.
A CloudArk solutions engineer will review your inquiry and email you within one business day with scheduling availability.