Build a private Llama chatbot with Ollama, Groq, Slack and Google Sheets

This workflow builds a fully private, self-hosted AI chatbot using Meta Llama models. Unlike cloud-based AI APIs, every conversation stays on your infrastructure — no data leaves your environment. The chatbot remembers conversation history per session, routes different query types to specialized Llama prompts, logs all interactions, and can escalate unresolved queries to a human agent via Slack.

Powered by Ollama (local) or Groq/Together AI (cloud Llama endpoints) — configurable in one node.

What's the Goal? To give businesses a production-grade private AI chatbot that: - Runs on their own servers with zero data exposure - Handles customer support, internal helpdesk, sales FAQs, and onboarding - Remembers context across a full conversation session - Routes intelligently: support vs sales vs general vs escalation - Logs every turn for quality review, training, and compliance

Why Does It Matter? Most businesses cannot send sensitive conversations to OpenAI or Anthropic due to: - GDPR, HIPAA, SOC2, or internal data governance policies - Confidential customer data in support queries - Proprietary internal knowledge that must stay private

Llama models run fully on-premise. This workflow gives those businesses the same quality AI chatbot experience with complete data sovereignty.

Monetization: sell this as a private AI chatbot deployment package to enterprises. Setup fee plus monthly hosting — recurring revenue.

How It Works

Stage A — Message Intake Webhook receives incoming chat message with session ID and user message text. Set node stores Llama endpoint config and normalizes the payload.