Building End‑to‑End Multi‑Agent Workflows with the OpenClaw Full‑Stack Template

Introduction

In today’s fast‑moving SaaS landscape, support teams are drowning in tickets while customers expect instant, accurate resolutions. A multi‑agent workflow that automatically classifies, prioritizes, and routes tickets can cut response times by up to 60 %.

The OpenClaw full‑stack template provides a ready‑made scaffolding for exactly this scenario. Built on the UBOS platform overview, it combines a Workflow automation studio, a Web app editor on UBOS, and pre‑configured integrations with leading LLM providers.

This guide walks developers, DevOps engineers, and product managers through the template architecture, shows how to craft a custom ticket‑routing assistant, and details the one‑click deployment process on UBOS.

OpenClaw Full‑Stack Template Architecture Overview

Core Components

• Agent Orchestrator – Coordinates multiple AI agents (e.g., classification, sentiment analysis, routing) using a directed acyclic graph.
• Data Layer – Persistent storage powered by Chroma DB integration for vector embeddings and a relational store for ticket metadata.
• Connector Hub – Ready‑made adapters for OpenAI ChatGPT integration, ChatGPT and Telegram integration, and other third‑party services.
• UI Layer – A responsive dashboard generated by the Web app editor on UBOS, allowing agents to be monitored in real time.
• Automation Engine – Executes conditional logic defined in the Workflow automation studio, such as escalation rules or SLA checks.

Data Flow Diagram (Simplified)

Ticket → Ingestion Service → Classification Agent → Sentiment Agent → Routing Agent → DB Write
    

The flow starts when a ticket arrives via email, web form, or chat channel. The Ingestion Service normalizes the payload and forwards it to the Classification Agent. The classification result (e.g., “Billing”, “Technical”) is enriched with sentiment scores before the Routing Agent decides the appropriate support queue. All decisions are persisted for audit and analytics.

Creating a Custom Ticket‑Routing Assistant Workflow

1. Defining the Problem

Before writing any code, clarify the business rules:

• Which ticket categories exist?
• What sentiment thresholds trigger escalation?
• Which support teams (e.g., Tier‑1, Tier‑2, Billing) should receive which tickets?

Document these rules in a markdown file stored in the repository; the UBOS templates for quick start include a rules.md example you can copy.

2. Designing the Agent Chain

OpenClaw’s template ships with three baseline agents. For a ticket‑routing assistant you’ll typically add a fourth “Priority Agent”. The chain looks like this:

1. Classifier – Uses a fine‑tuned OpenAI ChatGPT integration to assign a category.
2. Sentiment Analyzer – Calls the ElevenLabs AI voice integration (optional) to detect angry tones in voice tickets.
3. Priority Engine – Custom Python script that reads SLA data from the DB and boosts priority for VIP customers.
4. Router – Maps {category, priority} to a queue ID and pushes the ticket to the appropriate Slack or Teams channel.

3. Implementing the Workflow in OpenClaw

Follow these steps inside the Web app editor on UBOS:

# 1️⃣ Clone the OpenClaw template
git clone https://github.com/ubos/openclaw-template.git
cd openclaw-template

# 2️⃣ Install dependencies
pip install -r requirements.txt

# 3️⃣ Add a new agent file: priority_agent.py
#    (see UBOS documentation for the Agent SDK)

# 4️⃣ Register the agent in agents.yaml
- name: priority_agent
  module: priority_agent
  class: PriorityAgent

# 5️⃣ Update workflow.yaml to insert the new node
steps:
  - name: classify
    agent: classifier
  - name: sentiment
    agent: sentiment_analyzer
  - name: prioritize
    agent: priority_agent
  - name: route
    agent: router

After saving, the Workflow automation studio visualizer will display the updated DAG. Test the chain locally with python run_workflow.py --ticket sample.json and verify the output JSON contains queue_id and priority fields.

Deploying the Workflow on UBOS

Prerequisites

• UBOS account with UBOS pricing plans that include compute resources.
• Docker installed locally (UBOS uses container‑based deployment).
• Access token for the UBOS partner program if you need private repo support.

Step‑by‑Step Deployment

1. Login to UBOS CLI
   ubos login –api-key <YOUR_API_KEY>
2. Push the repository
   ubos push ./openclaw-template –app ticket‑router
3. Configure environment variables (e.g., OPENAI_API_KEY, CHROMA_DB_URL) via the UBOS dashboard under Enterprise AI platform by UBOS.
4. Trigger a build – UBOS automatically builds a Docker image, runs unit tests, and deploys to a managed Kubernetes cluster.
5. Expose the API – Use the built‑in Telegram integration on UBOS to receive tickets from a Telegram bot, or expose a REST endpoint for your CRM.

Verification

After deployment, run a quick sanity check:

curl -X POST https://api.ubos.tech/ticket-router \
  -H "Authorization: Bearer $UBOS_TOKEN" \
  -d '{"subject":"Unable to login","body":"My password reset link is broken"}'

The response should contain a queue_id (e.g., support‑billing) and a priority field. Open the UBOS dashboard, navigate to the UBOS portfolio examples, and you’ll see the ticket appear in the appropriate lane.

SEO and Internal Linking

Search engines reward content that naturally weaves relevant internal resources. In this article we linked to the OpenClaw hosting page, the AI marketing agents page, and the About UBOS page, among others. This creates a semantic web that helps both crawlers and readers discover related capabilities.

For further optimization, add structured data (JSON‑LD) to the page header (handled automatically by UBOS) and ensure the primary keyword “OpenClaw full‑stack template” appears in the title tag, meta description, and the first paragraph—as demonstrated above.