AI Maintenance & Support
Ongoing monitoring, model updates, and incident response so your AI integration stays working after go-live.
AI integrations require ongoing attention that conventional software doesn't: model versions are deprecated on provider timelines, not yours; output quality can shift when a provider updates a model; and usage costs can spike when a prompt change accidentally increases token consumption. Maintenance support covers all of this as a managed service.
We monitor live integrations for accuracy drift — a regular automated evaluation against a labelled sample that surfaces when output quality has changed without anyone noticing. When a provider deprecates a model, we handle the migration before the deadline, including regression testing on your data.
Incident response for AI-specific issues (unexpected outputs, provider outages, cost anomalies) is included. We also handle the routine work: prompt updates when your use case evolves, cost reviews as usage scales, and access to the integration for your team when questions come up.
What maintenance covers
Accuracy Monitoring
Regular evaluation against labelled samples — surfaces quality drift before your users notice.
Model Version Management
Provider deprecation handled before the deadline, with regression testing on your data.
Cost Monitoring
Usage tracked and anomalies flagged before they show up as a billing surprise.
Incident Response
Unexpected outputs, provider outages, and prompt regressions handled as a priority.