Customer Support AI Workflows

Workflows in this category

• Customer Support AI — Customer Support AI deflects tickets and assists agents by combining grounded retrieval, brand-voice tuning, escalation policies and live observability.
• Voice AI — Voice AI combines speech-to-text, an LLM and text-to-speech behind a low-latency turn-taking pipeline.
• RAG Support Bot — A RAG support bot retrieves the most relevant help-centre articles for each inbound query using semantic search, passes the retrieved context to a language model for grounded answer generation, and cites every source by article title and section.
• Ticket Triage — Classify, prioritise and route support tickets with a fine-tuned classifier + LLM rationale for transparent decisions.
• Auto Reply Generation — Draft empathetic, brand-tuned first responses for support agents with citations to the source knowledge.
• Escalation Workflows — Detect at-risk conversations and escalate with a structured handoff packet for the right specialist.
• Knowledge Base Generation — Mine resolved tickets and SME notes to generate, deduplicate and maintain a self-serve knowledge base.
• Call Summarization — Transcribe, summarise and extract action items from sales and support calls with speaker attribution.
• Support Analytics — Cluster ticket themes, surface emerging issues and explain weekly support trends to product and ops teams.
• Agent Assist — Agent assist surfaces real-time support to human agents during live customer conversations.
• Multilingual Support — Multilingual support detects the language of each inbound ticket, routes it to a locale-appropriate response model and enforces locale-specific escalation rules.
• Voice Support Agent — A voice support agent handles inbound tier-1 calls with speech-to-text transcription, real-time intent detection, and a RAG layer that retrieves policy and product information to ground responses.
• CSAT Prediction — Predict CSAT risk per ticket in real time and route at-risk conversations to senior agents with full context handoff.
• Self-Service Deflection — Self-service deflection classifies inbound questions against the help-centre taxonomy, retrieves the most relevant article or guided troubleshooting flow, and presents the result with an explainability note showing which keywords and intent signals drove the match.
• Conversation Quality Audit — Score every support conversation against your quality rubric with citations to the moments that drove the score.

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