ModelRefs / Support Stack

Support Stack

Customer support automation — RAG bots, triage, KB generation, escalation, analytics.

Overview

The support stack is opinionated: a grounded RAG bot handles first response, a triage classifier routes the long tail, and an analytics layer surfaces emerging issues. Confident escalation to a human is a first-class flow, not an afterthought.

Workflows in this stack

  • 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.
  • 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.
  • Policy Q&A Bot — Grounded Q&A over internal policies with citation, version awareness and an audit-ready answer log.
  • Patient Intake Bot — Conversational intake workflow that collects symptoms, history and consent into a structured chart-ready record.
  • Payer Policy Q&A — Retrieve versioned payer-policy passages and draft citation-grounded answers for qualified review, with freshness and jurisdiction gaps visible; no coverage, reimbursement, or authorization outcome is promised.
  • Onboarding Assistant — Conversational onboarding assistant grounded in policy, role-specific learning paths and IT setup tasks.
  • HR Policy Q&A — Self-serve HR policy Q&A with consistent answers, citation and escalation to HR business partners for sensitive cases.
  • Matter Intake — Capture prospective-client and matter facts into a restricted intake record, then route confidentiality, conflict-check, scope, engagement, and legal-advice decisions to authorized legal staff.

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Support Stack.