Documentation Index
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Sentinels Guide
Sentinels are VH3 AI’s proactive monitoring layer. They continuously analyse your operational data to detect emerging risks and growth opportunities — before they become entrenched problems or missed revenue. You discover SLA pain at month-end. The pattern was visible in week two. Sentinels close that gap.How sentinels work
Every sentinel is a pure database read — a structured query against your knowledge graph that evaluates a specific operational signal against configurable thresholds. There is no AI cost at the detection layer; intelligence is used only if you choose to generate a narrative explanation of what was detected.Detection
The sentinel query runs against your graph — looking for the pattern it’s designed to detect (e.g. repeat visits at a site exceeding threshold).
Scoring
Results are scored by severity. Each sentinel has a default threshold that determines what counts as a trigger vs. noise.
Configuration
Every sentinel supports these configuration parameters:| Parameter | Description |
|---|---|
threshold | Minimum severity to trigger (higher = fewer, more critical results) |
lookbackDays | How far back to analyse (default varies by sentinel) |
limit | Maximum results to return |
excludeFilters | Exclude specific engineers, sites, or customers from results |
Operational sentinels
Thirteen operational sentinels monitor for emerging risks across engineers, sites, customers, and SLAs:Engineer performance slip
Detects engineers whose SLA punctuality or completion quality has degraded compared to their historical baseline. Catches problems early — before a pattern becomes a client complaint.Site deterioration
Identifies sites where fault frequency or repeat visits are trending upward. Surfaces sites that may need a planned maintenance visit rather than continued reactive attendance.SLA breach cluster
Finds concentrated SLA breaches — by geography, engineer, customer, or time period. Distinguishes between isolated misses and systemic problems.Scheduling drift
Flags jobs where planned vs. actual timings are diverging — catch planning assumptions that no longer match reality.Data quality issues
Surfaces anomalies in job records that may indicate extraction or ingestion problems — keep your intelligence layer clean.Growth opportunity sentinels
Six growth sentinels surface revenue opportunities hiding in your operational history:Dormant customer
Identifies customers with no recent job activity who previously had regular engagement — potential re-engagement or churn risk before they formally leave.Overdue service interval
Flags equipment or sites that have passed their recommended service interval — maintenance contract upsell opportunities.Single-service cross-sell
Finds customers using only one service line when your business offers multiple — cross-sell candidates with evidence of engagement.Engineer-flagged follow-up
Surfaces jobs where engineers noted “follow up,” “recommend,” or “return visit” — quotes that should have happened but might have been missed.Seasonal buying patterns
Identifies customers whose service rhythms suggest upcoming seasonal needs — proactive outreach before they call someone else.Geographic upsell clusters
Finds neighbourhoods where one scheduled visit would make multiple nearby follow-ups economical — route density opportunities.Automation
Sentinel results are most powerful when routed automatically. Common patterns:- Daily Slack digest — summary of all sentinel triggers posted to an ops channel each morning
- Email alerts — critical sentinels (SLA breach cluster, site deterioration) sent to account managers immediately
- Weekly report inclusion — sentinel results embedded in weekly operational reports
- Case creation — high-severity triggers automatically create a case for follow-up
- WhatsApp notifications — urgent alerts routed to field managers on the move