The work in plain language
Notice the change. Know who responds.
Managed AI support is an agreed service for maintaining and monitoring deployed AI workflows, integrations and knowledge dependencies. Paloren scopes coverage, incident handling, evaluation and controlled updates around the system and its business owner. It can include source-freshness checks and output-quality reviews as well as technical faults. Coverage hours and response expectations are contractual decisions, not universal promises. New functionality, major remediation and third-party responsibilities are identified separately. Existing systems may need an acceptance review before support begins, particularly where documentation or operational access is incomplete.
01 / 04Managed AI support
Define what is being supported before promising coverage
Managed AI support starts with a service inventory and an agreed responsibility boundary. Paloren identifies the workflows, environments, integrations and information sources covered by the engagement. The scope distinguishes a defect in the implemented system from a third-party outage, an access request or a new feature. Support hours, response expectations and escalation contacts are agreed for the actual business need. No round-the-clock coverage or guaranteed resolution time is implied by this page. A system inherited from another supplier may need an initial review before support can be accepted. Clear boundaries make it possible to respond usefully without leaving critical dependencies between unaccountable parties.
- Supported workflow and environment inventory
- Defect, access, supplier and feature boundaries
- Agreed coverage hours and escalation contacts
02 / 04Managed AI support
Monitor usefulness as well as technical availability
An AI workflow can be technically available while producing poor or outdated work. Support monitoring therefore needs more than uptime. Depending on the scope, checks can include source freshness, failed integrations, rejected outputs, review queues and unexpected operating cost. The business owner helps define what deserves investigation and what normal variation looks like. Representative evaluation tasks provide a way to detect changed behaviour after an update. Monitoring should collect only the information required for its purpose, with agreed access and retention. Sensitive content does not need to be copied into every diagnostic record. The objective is actionable evidence, not a dashboard that produces alerts nobody owns.
- Freshness, integration and exception checks
- Representative output evaluation
- Alert ownership with proportionate diagnostic records
03 / 04Managed AI support
Triage incidents with a safe operating response
Support triage begins with the effect on the workflow and the people relying on it. The response may be to pause an automated action, switch to an existing manual process or restrict a source while evidence is examined. We document who can make those decisions and how the business is informed. Investigation separates the reported symptom from a confirmed cause. Relevant execution records and example outputs are preserved under agreed handling rules. Recovery is tested before normal operation resumes. Where an external action cannot be reversed, the response focuses on containment and remediation rather than pretending every incident can be solved by restoring a previous software version.
- Impact-based incident triage
- Pause and manual-fallback procedures
- Recovery checks and business communication
04 / 04Managed AI support
Make maintenance and improvement separate decisions
AI maintenance includes reviewing source changes, testing approved updates and keeping operating instructions usable. A change to a prompt, model, integration or permission can affect behaviour, so the support plan defines proportionate regression checks and release approval. Routine service reviews examine incidents, repeated exceptions and maintenance debt. They can also identify opportunities for improvement, but a new workflow or expanded action authority should not enter production as an informal support request. The handover and exit plan cover documentation, access ownership and outstanding work. Support should reduce dependence on undocumented knowledge while keeping the business able to choose who operates the system in future.
- Controlled updates with regression evidence
- Service review separating maintenance and new scope
- Documentation and access handover for continuity
What you take forward
A working result. And the means to keep it useful.
Supported-service inventory
Coverage and responsibility matrix
Monitoring and evaluation plan
Incident and fallback runbook
Controlled maintenance records
Service review and handover documentation
- 01
Review the service
Inventory workflows, dependencies, documentation and current operating risks.
- 02
Agree coverage
Define support boundaries, hours, contacts and incident priorities.
- 03
Operate and maintain
Monitor agreed signals and apply controlled, tested updates.
- 04
Review continuity
Examine recurring issues, new scope and documentation or exit needs.
Before we begin
Your questions.
Straight answers.
Do you provide 24-hour support?
This page does not promise 24-hour coverage. Required hours, response expectations and escalation arrangements must be agreed against the workflow's operational importance. If the business needs continuous coverage, that requirement should be raised before a proposal or service acceptance decision.
Can you support a system another supplier built?
Potentially, after reviewing the code or configuration, documentation, access and dependencies within an agreed assessment. Missing ownership or unsupported components may need remediation first. We should not promise dependable support for a system whose behaviour and operating boundaries have not been established.
Are new features included?
Only if the support agreement explicitly includes them. Routine maintenance and a new workflow involve different planning and acceptance work. Requests that expand data access, integrations or action authority should receive a separate scope and approval rather than being treated as an ordinary support ticket.
How do you handle changes in AI output quality?
The support plan can include representative evaluation tasks and review of rejected outputs. A change triggers investigation into sources, instructions, integrations or model behaviour. The response may be a tested update, a restricted workflow or a pause, with the business owner involved in the decision.
Your team. Your next chapter.