AI Agent Workflow — LLM-Powered Classification, Generation & Routing
Describe what you need AI to decide, classify, or generate. Get a workflow with LLM nodes wired into your automation — prompts tuned, outputs parsed, actions triggered.
What's in Your AI Agent Workflow
A complete automation with LLM intelligence baked in. AI classifies, generates, or decides — then triggers the right downstream actions based on the result.
LLM Node Configuration
Pre-configured AI nodes with optimised prompts, model selection, temperature settings, and output parsing.
Decision Routing
AI classification output routes data to the right path — support vs sales, urgent vs normal, positive vs negative.
Content Generation
AI generates responses, summaries, translations, or analyses — then feeds them into downstream actions.
Output Parsing
Structured output extraction from LLM responses — JSON parsing, field extraction, and validation.
Fallback Logic
When AI confidence is low or the API fails, fallback paths route to manual review or default actions.
“AI classifies our support tickets into 8 categories with 94% accuracy. What took a human 30 seconds per ticket now happens instantly for 500+ tickets a day.”
AI Agent Workflow Use Cases
Intelligent Email Triage
New email → AI classifies intent and urgency → routes to correct department → generates suggested response → notifies assignee with context.
Build this workflowSupport Ticket Classification
New ticket → AI categorises issue type → assigns priority → suggests knowledge base articles → routes to specialist team.
Build this workflowContent Moderation Pipeline
User-generated content → AI checks for policy violations → auto-approve clean content → flag borderline for review → auto-reject obvious violations.
Build this workflowLead Qualification
New lead → AI analyses company data and signals → scores lead quality → routes hot leads to sales → adds cold leads to nurture sequence.
Build this workflowExample AI Agent Workflow Output
Here's a preview of the AI workflow structure you'll receive:
# AI Workflow: Support Ticket Classification + Routing
## Trigger: New Zendesk Ticket (webhook)
## Node 1: AI Classification (Claude Sonnet)
Prompt: |
Classify this support ticket:
Subject: {{subject}}
Body: {{body}}
Return JSON:
{ "category": "billing|technical|feature|account",
"priority": "critical|high|medium|low",
"sentiment": "positive|neutral|negative" }
Temperature: 0.1
Max tokens: 200
## Node 2: Parse JSON Response
Extract: category, priority, sentiment
## Node 3: Route by Category
- billing → assign to billing team
- technical → assign to engineering
- feature → log to feature request board
- account → assign to account management
## Node 4: Priority Escalation
- critical + negative → page on-call engineer
- critical → notify team lead
- high → standard assignment
- medium/low → queue for next availableSimplified preview — actual workflows include complete LLM configurations, prompt engineering, output parsing, error handling, and platform-specific JSON.
From $25 AUD · Prototypes in ~90 seconds
How to Get Your AI Agent Workflow
Describe the intelligence
Tell us what the AI should classify, generate, or decide — and what downstream actions to trigger.
Compare AI workflow designs
AI agents build competing workflows with different LLM strategies. Review them side-by-side with quality scores.
Import and activate
Import the workflow, add your LLM API key, and watch AI intelligence power your automation.
Why Custom AI Workflows Beat Manual Prompt Integration
Prompts pre-optimised
System prompts tuned for classification accuracy, structured output, and low hallucination. Not generic prompts pasted into a node.
Output parsing included
LLM outputs are parsed, validated, and transformed into structured data that downstream nodes can consume reliably.
Fallback logic built in
When AI confidence is low or the API fails, the workflow doesn't just stop — it routes to manual review or applies default actions.
AI Agent Workflow — Common Questions
Which LLM providers are supported?
OpenAI (GPT-4o, GPT-4), Anthropic (Claude Sonnet, Haiku), Google (Gemini), and any provider with a REST API. The workflow includes pre-configured prompts optimised for your chosen model.
Which automation platforms support AI nodes?
n8n has native OpenAI and HTTP nodes for any LLM. Make.com has OpenAI and HTTP modules. Zapier has ChatGPT integration and webhook steps. All platforms are supported.
How reliable is AI classification?
With properly structured prompts and low temperature settings, classification accuracy typically exceeds 90%. The workflow includes confidence thresholds — low-confidence results route to manual review.
Can the AI generate content, not just classify?
Yes. AI nodes can generate email replies, summaries, translations, product descriptions, social posts, or any text content — then feed it into downstream actions.
What about LLM API costs?
The workflow is optimised for cost — using smaller models where accuracy is sufficient, batching requests where possible, and caching repeated queries. Estimated API costs are documented.
What if the LLM API is down?
Fallback logic queues items for retry, applies default routing rules, or sends to manual review. Your automation doesn't stop because of an LLM outage.
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