Loris

Analyzes customer sentiment during live conversations and provides immediate emotional tone detection. Identifies shifts in customer mood from positive to negative or vice versa, allowing agents to recognize escalation risks as they develop.

Generates contextually appropriate response suggestions for support agents based on the current conversation state and customer sentiment. Provides multiple response options tailored to de-escalate or maintain positive tone.

Recommends specific de-escalation strategies and communication tactics during tense customer interactions. Provides actionable guidance on how to calm frustrated customers and redirect conversations toward resolution.

Provides real-time coaching to agents about their own communication tone and how to adjust it based on customer sentiment. Alerts agents when their tone may be mismatched with customer emotional state.

Guides agents toward resolving customer issues on the first contact by providing relevant information, suggested solutions, and communication strategies in real-time. Reduces the need for follow-ups or escalations.

Predicts customer satisfaction outcomes based on conversation patterns and sentiment trajectory, alerting agents to interactions at risk of low satisfaction scores. Enables proactive intervention before negative feedback occurs.

Seamlessly embeds AI coaching and guidance directly into the support agent's workflow without requiring context switching. Delivers insights and suggestions within the chat interface or ticketing system agents already use.

Identifies conversations at high risk of escalation based on sentiment trends, customer language patterns, and interaction history. Alerts agents before a situation becomes critical.

Provides agents and managers with post-conversation analytics and coaching insights based on sentiment, tone, and resolution effectiveness. Enables continuous improvement through data-driven feedback.