Customer support · Production

Freddy AI Copilot delivers 67% response quality improvement and 60% agent productivity improvement

The problem

Customer support agents had to compose responses from scratch, lacked real-time context in long ticket threads, could not effectively serve multilingual customers, and had no visibility into customer sentiment in time to prevent escalations.

Workflow diagram · grounded in source
1
Sentiment detection and tagging
ai_action
“La inteligencia de sentimientos detecta la frustración, la urgencia o la confusión en tiempo real y etiqueta las consultas como positivas, neutrales o negativas para que los agentes puedan responder con empatía y evitar que las situacion…”
2
Thread summarization
ai_action
“Póngase al día al instante con resúmenes inteligentes y contextuales. Responda con confianza, sin demoras en derivaciones ni escalaciones”
3
AI response drafting
ai_action
“Cree respuestas redactadas, claras y alineadas con su marca al instante usando los datos del ticket y la conversación, para que sus agentes nunca tengan que empezar desde cero. Ajuste su respuesta para que coincida con su tono”
4
KB-based resolution suggestions
ai_action
“Al basarse en artículos de la base de conocimientos y tickets históricos, Freddy AI brinda sugerencias de respuesta en tiempo real que minimizan el esfuerzo manual, mejoran la consistencia y aceleran los tiempos de resolución”
5
Real-time translation
ai_action
“traducción en vivo en más de 60 idiomas, hable con los clientes en cualquier lugar de su voz”
Reported outcome

Freddy AI Copilot delivered 67% improvement in response quality, 60% improvement in agent productivity, and 56% time saved with summary assistance.
Customer testimonials confirm significant time savings on conversation and escalation management and improvement in everyday interactions.

Reported metrics
Response quality improvement67%
Agent productivity improvement60%
Time saved with summary assistance56%
Agent time saved on conversation managementhemos ahorrado mucho tiempo para nuestros agentes
Reported stack
Freddy AI CopilotFreddy AIFreshdesk OmniAI Agent Studioentrenador de calidad
Source
https://www.freshworks.com/latam/freshdesk/omni/freddy-ai-copilot/
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Freddy AI Copilot delivered 67% improvement in response quality, 60% improvement in agent productivity, and 56% time saved with summary assistance.

What tools did this team use?

Freddy AI Copilot, Freddy AI, Freshdesk Omni, AI Agent Studio, entrenador de calidad.

What results were reported?

Response quality improvement: 67%; Agent productivity improvement: 60%; Time saved with summary assistance: 56%; Agent time saved on conversation management: hemos ahorrado mucho tiempo para nuestros agentes (source-reported, not independently verified).

How is this customer support AI workflow structured?

Sentiment detection and tagging → Thread summarization → AI response drafting → KB-based resolution suggestions → Real-time translation.

Related customer support cases