Workflow
Build a Tier-1 Customer Support Agent
An agent that handles common tickets end-to-end and hands off the rest.
1 min readupdated 2026-07-04
/ quick answer
Wire a RAG-grounded agent with tools for order lookup, refund, and human handoff. An agent that handles common tickets end-to-end and hands off the rest.
An agent that handles common tickets end-to-end and hands off the rest. The problem it solves: Support teams drown in repetitive tickets that already have canonical answers in the KB. Wire a RAG-grounded agent with tools for order lookup, refund, and human handoff. It runs in 5 steps, starting with ingest kb, macros, and last 12 months of resolved tickets into a vector store. This workflow node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.
Problem
Support teams drown in repetitive tickets that already have canonical answers in the KB.
Solution
Wire a RAG-grounded agent with tools for order lookup, refund, and human handoff.
Steps
- 01Ingest KB, macros, and last 12 months of resolved tickets into a vector store.
- 02Define tools: search_kb, get_order, issue_refund_under_50, escalate_to_human.
- 03Prompt the agent to always cite KB chunks and refuse if confidence is low.
- 04Wire evals over 200 historical tickets and require >90% grounded accuracy before shipping.
- 05Deploy behind a feature flag; monitor CSAT and handoff rate weekly.
Tools Used
Prompts Used
Variations
- Add a proactive outreach mode for shipping-delay tickets.
Related Dictionary
/ frequently asked
What does the Build a Tier-1 Customer Support Agent workflow do?
Wire a RAG-grounded agent with tools for order lookup, refund, and human handoff.
What problem does Build a Tier-1 Customer Support Agent solve?
Support teams drown in repetitive tickets that already have canonical answers in the KB.
How many steps does Build a Tier-1 Customer Support Agent take?
5 steps. It starts with ingest kb, macros, and last 12 months of resolved tickets into a vector store. and ends with deploy behind a feature flag; monitor csat and handoff rate weekly..
Which tools does Build a Tier-1 Customer Support Agent need?
It uses ai-support-agent-stack, rag-starter-stack — each linked below with its own node.
↳ connected nodes
Dictionary↳ linked
RAG (Retrieval-Augmented Generation)
Inject external knowledge into an LLM at query time.
Dictionary↳ linked
Agentic Workflow
A workflow where an LLM decides the next step instead of a hard-coded path.
Dictionary↳ linked
Evals
Automated tests that grade LLM outputs against expected behavior.
Tool Stack↳ linked
AI Support Agent Stack
Tier-1 support handled by an AI agent grounded on your docs, with human handoff.
Tool Stack↳ linked
RAG Starter Stack
Minimum viable stack to ship a production RAG chatbot.
Prompt↳ linked
Grounded Answer Prompt
Force the model to answer only from provided sources, with citations.
Use Case↳ linked
SaaS Support Team Automates Tier-1, Focuses on Retention
Support org deflects 55% of tickets and re-invests the time into proactive retention.
Dictionary↳ linked
Agent Architecture
Agent architecture is the structural blueprint of an AI agent: the model, the planning loop, the tools, the memory layer and the guardrails that decide how it acts.
Workflow↳ linked
Telephony AI Voice Integration
Telephony AI Voice Integration is a workflow that connects AI voice agents with traditional phone systems to automate customer interactions, providing scalable and efficient support.
Workflow↳ linked
Build AI Voice Agent Customer Support
This workflow outlines the steps to develop and deploy an AI voice agent for automated customer support interactions, from intent recognition to natural language response generation. It aims to reduce agent workload and improve response times for common queries.
Workflow↳ linked
Multi-Agent Customer Support
This workflow outlines how CrewAI can be used to build a multi-agent customer support system that automates inquiry routing, resolution, and escalation, improving response times and customer satisfaction.