Xect AI connects business activity, customer contacts, and service performance into one event stream. ML Anomaly Detection flags a deviation, the Correlation Agent confirms it as an incident, and the Dispatcher Agent runs the matching response, so dashboards stop being the last to know.
Business KPIs get reviewed the next morning, static thresholds page people on payday and go quiet on the real dip, and the map, the chart and the ticket queue live in three different tools. Xect AI turns the events already flowing through the Business Hub into monitored streams that agents watch for deviations, correlate into a confirmed incident, and act on through the matching response flow.
Detection watches per stream, calls and tickets watch per hub, and QoS watches per hub, all from the same underlying events.
Deviations across streams and places collapse into one situation with a likely cause.
Within policy, the matching playbook runs automatically: failover, proactive fix, customer actions, NOC ticket. Outside policy, it pauses for approval.
The same monitors confirm recovery; the record closes itself.
Each agent owns one stage of the watch-to-verify path above, across all four observability surfaces.
One agent per surface: anomaly detection, the map, QoS
A dedicated watcher runs against each event stream through anomaly detection, against calls and tickets per hub on the live map, and against measured-versus-provisioned service speed per hub through QoS, all reading from the same underlying events instead of three separate pipelines.
Turns three separate deviations into one situation
Reads what every watcher agent flags, checks it against the knowledge graph of hubs, streams and recent changes, and collapses the pattern into a single situation with a likely cause instead of three unrelated alerts.
Opens the flow, pauses when policy says so
Opens the remediation flow that matches the correlated cause, a failover, a proactive fix, a customer action or a NOC ticket, and pauses for approval when the action exceeds policy. The same monitors it triggered confirm recovery and close the record.
Detection flags the deviation, the map places it live by hub, Location Intelligence rolls it up by address for planning, and Proactive Fix runs the remediation.
Every business event stream gets its own model, trained on its own seasonal pattern, so a dip that is normal on a Sunday does not page anyone and a dip that is not gets caught in minutes.
Explore ML Anomaly DetectionCalls and trouble tickets place on the same map, against the same thresholds the operations team already trusts, so a hub climbing toward trouble is visible before it pages anyone.
Explore the mapEvery serviceable location and every hub carries its own rolling day of metrics, so a planner or a field lead reads the same map at the zoom level their job actually needs.
Explore Location IntelligenceOnce a hub's quality of service score slips, the matching fix runs automatically and the same score confirms the fix worked, before a customer calls in about it.
Explore Proactive FixFour surfaces, one event stream, agents on every one of them.
When call volume climbs in a hub before an outage ticket exists, Xect AI flags the deviation, correlates it against the network change log, and opens the incident before the queue does.
See the industry pageWhen checkout success drops during a flash sale while every server metric stays green, Xect AI's payment stream model flags the business-level failure and routes it before shoppers start abandoning carts.
Talk to us about e-commerceWhen scan events slow and dwell time climbs at one hub, Xect AI correlates the pattern against nearby hubs and opens a proactive fix before the delay reaches the customer.
Talk to us about logisticsWhen scheduling requests or portal logins drop against their modeled pattern, Xect AI flags the deviation as a business event, not just a system metric, and routes it to the team that owns it.
Talk to us about healthcare operationsWhen sign-ups, payments or logins deviate from their modeled baseline, Xect AI catches the business impact before a churn dashboard does, and opens the fix flow automatically.
Talk to us about SaaSOwns revenue and margin across every channel, and needs to know the moment a business event stream breaks pattern, not read about it in next month's board deck.
Owns uptime and the on-call rotation, and needs calls, tickets and QoS on one live map instead of stitching three tools together mid-incident.
Owns handle time and staffing, and needs to see a hub's calls climbing before it turns into a queue nobody staffed for.
Owns the models behind every stream, and needs each one versioned, explainable and retrained on schedule, not a black box the business stops trusting after one bad alert.
Book a 30-minute demo and see a deviation move from detection to confirmed incident to completed response on your own event streams.