Hi! We’re looking for someone who can build a reliable AI automation system that helps us automatically classify/tag, enrich, and route inbound leads/messages using LLM integration (OpenAI/LLMs) inside a structured workflow.
This is not a basic “trigger → action” setup. We need a clean, scalable build with validation, error handling, and clear documentation.
What we want to automate
AI chatbot integration into automation workflows (simple chat intake or message processing via webhook)
Classification / tagging automation: use an LLM to label intent (sales/support/other), urgency, topic, and next step
AI-powered data extraction and enrichment via API integration (pull key fields, normalize data, optional automated enrichment)
Route to the right workflow and push clean data into our systems (CRM/database/spreadsheet)
Optional: light content automation (draft replies, summaries, internal notes) with guardrails
Tools / stack
Workflow orchestration: n8n or Make.com (Zapier ok if justified)
API-based AI integration using webhooks + REST APIs
Data processing layer can be Airtable / Notion / Google Sheets (open to your recommendation)
What success looks like
A production-ready AI workflow / AI pipeline that runs consistently
Clean logging + retries + safe fallbacks when the AI/API fails
Short handoff docs: “what triggers what,” and where the data lives (design and implement AI workflow pipeline with documentation)
To apply, please include
Which tool you prefer: n8n, Make.com, or Zapier
1–2 relevant examples (AI workflows, chatbots, AI agents, data extraction, classification)
Any experience with scalable AI workflows and debugging edge cases
Start your proposal with “AI-WORKFLOW” so I know you read this
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