At a Glance
AI Escalation Manager adds a predictive layer to your support workflow, detecting high-risk cases early on, routing them to the right agents, and alerting managers in real time, so you resolve cases faster, avoid SLA breaches, and prevent customer churn.
What it solves?
How is it deployed?
What can it do?
Who is it for?
Built to Prevent, Not Just React
01
Proactive Escalation Detection
Identify and flag high-risk cases early using AI models trained on sentiment, SLA breaches, and complexity indicators.
02
Skill-Based Routing for Faster Resolutions
Assign critical cases to the most qualified agents based on expertise, experience, availability, and past resolution success.
03
Real-Time Alerts for Critical Cases
Send instant alerts to managers through Slack, email, or WhatsApp when escalation probability crosses defined thresholds.
04
Intelligent SLA Monitoring
Track SLA response and resolution targets in real time to prioritize cases that need urgent attention.
05
Lower Escalation Volume, Higher CSAT
Reduce firefighting with early interventions—leading to faster resolutions, fewer escalations, and improved customer satisfaction.
06
360° Escalation Analytics
Access dashboards that reveal escalation patterns, agent performance, and sentiment impact to continuously improve operations.
07
Customizable Escalation Logic
Adjust scoring models, thresholds, and routing logic to match your internal policies and escalation categories.
Drive Measurable Outcomes Across Support Operations
From reducing firefighting to boosting CSAT, AI Escalation Manager delivers quantifiable results that transform how your support team handles risk—at scale and in real time.
Fewer Escalations
- Early detection of high-risk cases
- Up to 45% reduction in escalation volume
Faster Resolutions
- Skill-based agent routing
- 20–30% drop in average resolution time
Higher SLA Compliance
- Real-time SLA breach monitoring
- Instant alerts for at-risk cases
Improved First Contact Resolution
- Intelligent triage and prioritization
- 15–25% increase in FCR
Happier Customers
- CSAT uplift of 10–20%
- Fewer delays, less frustration
Industry Recognitions
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Frequently Asked Questions
Yes. It uses sentiment shifts, SLA patterns, case complexity, and customer history to predict escalation risk with high precision.
Absolutely. You can tailor thresholds, rules, routing flows, and even sentiment weightings to reflect your internal escalation policies.
Seamless integration via API or prebuilt connectors with platforms like Salesforce, Zendesk, ServiceNow, Jira, and Slack.
Managers can manually override escalations. These corrections are fed back into the model for supervised learning and continuous improvement.
Most teams report reduced escalations and improved SLA performance within 4–6 weeks. Predictive accuracy improves further as the model learns from your data.
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