Brilo AI Uptime Tracking reports platform availability for voice agent call handling as the percentage of time the system is reachable and able to process calls. Brilo AI’s platform target is generally 99.9% availability; for customer-specific service-level agreements (SLA), historical uptime, or contractual remedies, contact your Brilo AI account manager or Support. Uptime Tracking combines automated health checks, telemetry, and incident reporting to detect outages and compute availability and related metrics such as mean time to repair (MTTR) and concurrency. These measurements help you plan capacity for high-concurrency events and evaluate incident impact on call handling.

How do you measure system availability? — Brilo AI: Uptime is calculated as the percent of time the system can handle calls within a reporting window.

Is platform uptime the same as an SLA? — No: SLAs are contractual and may differ from Brilo AI’s general availability target; request a customer-specific SLA for firm commitments.

How does Brilo AI report outages? — Brilo AI generates incident reports and aggregates MTTR and uptime metrics for the requested date range.

Platform administrators, procurement teams, and technical leads ask about Uptime Tracking because voice availability directly affects caller experience in regulated sectors such as healthcare and banking. Missed or delayed calls during peak periods can cause operational, compliance, and reputational risk. Buyers need clear measurement methods to compare solutions, plan capacity, and request contractual protection such as SLAs or incident reporting for audits and vendor risk reviews.

Brilo AI measures uptime by running continuous health checks across the voice pipeline (API endpoints, media processing, and routing layers), collecting telemetry, and recording service reachability. The uptime percentage is computed over a selectable reporting window and excludes scheduled maintenance when that maintenance is published per your contract.

In Brilo AI, uptime is the percentage of time the platform is reachable and able to accept and process calls for the configured phone flows.

In Brilo AI, concurrency is the number of simultaneous active call sessions the platform handled during a time window; tracking concurrency helps size capacity for campaigns.

Brilo AI captures events (failed health checks, API errors, degraded media) and surfaces them in incident reports to compute mean time to repair (MTTR) and availability trends.

Brilo AI’s Uptime Tracking measures platform-level availability and depends on multiple factors outside the platform, such as customer network health, carrier or PSTN connectivity, and customer firewall configuration. Brilo AI does not assume responsibility for third-party carrier outages or on-premises network faults unless otherwise specified in a customer SLA.

In Brilo AI, an incident is a logged event or set of events that materially reduce service availability or functionality and that triggers incident response and post-incident reporting.

Brilo AI will escalate issues according to configured monitoring thresholds and incident response playbooks, but it will not automatically remediate customer-side network or carrier issues.

For details about escalation behavior and when the AI triggers a human handoff or escalation based on confidence and intent detection, see the Brilo AI human handoff and intent routing guidance: Brilo AI how the AI understands what the caller wants and escalation rules.

When incidents impact availability or when the AI detects low-confidence intent during a call, Brilo AI workflows can escalate to a human agent or alternate routing. Escalation rules can be based on confidence thresholds, specific detected intents, or explicit caller requests for a human. Brilo AI passes context (transcript excerpt, detected intent, and extracted entities) to the human agent to avoid repeated questions and speed resolution. Configure warm transfer, cold transfer, or callback handoff rules in the agent’s escalation settings so handing off remains predictable during degraded conditions.

For guidance on tuning accuracy and intent detection that affect escalation behavior, see the Brilo AI accuracy and intent tuning guide: Brilo AI how accurate are AI voice agents?

Consistent Uptime Tracking with clear incident reporting helps reduce missed calls, improves planning for high-concurrency events, and provides evidence for vendor risk assessments. Operational teams gain predictable capacity planning data and incident timelines for audit and remediation. Uptime metrics also support conversations with Brilo AI for scaling or SLA adjustments when your usage profile changes.

What uptime percentage does Brilo AI guarantee?

Brilo AI’s platform target is generally 99.9% availability. For a binding guarantee, request a customer-specific SLA from your Brilo AI account manager or Support.

Does scheduled maintenance count against uptime?

Scheduled maintenance is typically published and excluded from uptime calculations when it is part of agreed maintenance windows or notified per your contract. Check your contract or ask Support for how maintenance windows are handled for your account.

How quickly will Brilo AI report an incident?

Brilo AI uses automated health checks and telemetry to detect outages and will notify configured contacts based on your alerting settings. For contractual response times or incident timelines, request the SLA or incident reporting details for your account.

Can Brilo AI push uptime metrics to my monitoring system?

Yes — you can forward telemetry and incident events to your webhook endpoint or logging destination. Configure webhooks in the Brilo AI console and validate event delivery during setup.

Will Brilo AI resolve carrier or PSTN outages?

No. Brilo AI will surface carrier- or network-related failures in incident reports, but carrier/PSTN connectivity and customer network faults are outside Brilo AI’s direct control unless a managed service agreement explicitly states otherwise.