TBW / AI SERVICES / MONITORING, TRAINING AND ONGOING SUPPORT
Monitoring, Training and Ongoing Support
Operate AI systems with ongoing evaluation, monitoring, change control, incident readiness and team enablement.
A Controlled Path to Outcomes
Begin with a named service owner and a baseline for quality, availability, cost and risk. Define who reviews alerts, approves changes and can stop an unsafe workflow; operational evidence should guide each release decision.
Our Approach
Establish representative evaluation cases and alert thresholds for the deployed workload. Review monitored traces and exceptions with operators, rehearse rollback and credential revocation, then update runbooks and training as the system changes.
What to Watch
Observe latency, errors, tool calls, retrieval and answer quality, guardrail events, cost, index freshness and provider or model changes. Tune telemetry to avoid exposing sensitive payloads.
Production Evaluation
Sample authorized interactions, score against agreed criteria, run representative test sets after changes and review regressions and trends. Route consequential failures to human review.
Change Management
Version prompts, models, embeddings, routing and configuration. Evaluate changes in staging, use staged release and retain a rollback path with named approval.
AI Incident Response
Document how to disable a workflow with a kill switch, revoke a tool credential, disable a model route or roll back. Preserve appropriate evidence, contain exposure and conduct post-incident review.
Support Options
Choose advisory guidance, monitoring and reporting, or hands-on operations by agreed scope and ownership. Response arrangements require separate agreement; this page does not promise an SLA.
Business Reporting
Review quality, availability, cost, risks, incidents and an improvement backlog with decision owners. Report limitations and trends, not just activity counts.
Role-Based Training
Tailor training for operators handling alerts, admins managing access and changes, developers maintaining evaluations, and business users recognizing limits and escalation paths.
Regular Review Rhythm
Hold regular reviews of quality, risk, incidents and the backlog at a cadence suited to the system. Reassess the plan when use, model behavior or business priorities change.
Handover and Exit
Keep documentation, credential ownership, system ownership, export routes, runbooks and transition responsibilities current so the client can continue or change operators without a hidden dependency.
Operational Deliverables
Dashboards, evaluation reports, operational runbooks, incident procedures, training material and an improvement backlog. Related: Training · AI Implementation · Consulting.
Controls and Accountability
Assign an owner for evaluation trends, alert triage, model-route changes and incident actions. Preserve operational evidence while limiting sensitive telemetry, and rehearse escalation and recovery.
Frequently Asked Questions
What does ongoing evaluation measure?
Representative answer quality, retrieval performance, failures and regressions against agreed criteria.
Can an unsafe workflow be stopped quickly?
A documented kill switch, credential revocation and route disablement should be tested for the specific deployment.
Do support options include a guaranteed response time?
No SLA is promised here; scope and response arrangements must be agreed separately.
Who needs training?
Operators, administrators, developers and business users need different guidance and escalation paths.
What happens if support ends?
Provide current runbooks, ownership, credentials and export or transition information to the designated owner.
Plan the Next Step
Bring a deployed workflow, its monitoring and evaluation evidence, and the team that operates it. We can define review, incident and handover responsibilities for that specific system.