10 LLM Agents Every Small Business Can Run on Self-Hosted n8n

Crzy undefined (undefined) — Tue, 13 Oct 2026 07:51:08 +0000

You don't need an agent framework to get value from LLMs. Most useful "agents" for a small business are one structured call inside a workflow you already trust. Here are 10 I run on self-hosted n8n, and the pattern behind all of them.

The pattern

Trigger: a webhook or a schedule.
Build Prompt: a Code node with a strict system prompt and a JSON output contract.
LLM: an HTTP Request to any OpenAI-compatible /chat/completions, in JSON mode, with 3 retries.
Parse: safe JSON.parse with a fallback.
Act: Slack, Sheets, a CRM, or a webhook response.

The 10

Lead qualifier: BANT score, Slack alert for hot leads.
Support FAQ agent: answers only from your KB, escalate flag for humans.
Cold email personalizer: ≤110 words, no invented facts.
Invoice extractor: vendor, totals, GSTIN, line items, with null instead of guesses.
Daily market digest: RSS → the 5 items that matter, plus one action.
Meeting notes → actions: decisions, owners, due dates.
Review replies: sentiment and a brand-safe reply.
Content repurposer: blog → LinkedIn, X thread, newsletter, SEO meta.
Resume screener: evidence-only scoring with bias guardrails, human in the loop.
Weekly metrics narrator: JSON metrics → a plain-English Monday brief.

Lessons

Ask for JSON and say what to do when data is missing ("use null, never guess"). That one line removes most hallucinations in extraction tasks.
Keep the model swappable. A Config node holding baseUrl and model lets you move between a paid API and local Ollama in seconds.
Put humans on outbound actions. Draft, don't auto-send.

Grab them

Two of these workflows are free on GitHub, with import instructions: https://github.com/arkintof/n8n-ai-agent-workflows

Which of these would you trust to run unattended, and which would you keep a human on? Tell me in the comments.

Written with AI assistance; workflow built and tested by me.

Build an AI Lead Qualifier in n8n in 15 Minutes (Free Workflow)

Crzy undefined (undefined) — Mon, 12 Oct 2026 22:56:58 +0000

Inbound leads go cold while you're busy. Here's a 5-node n8n workflow that scores every form submission with an LLM and pings Slack only for the leads worth your time.

The flow

Webhook → Config → Build Prompt → LLM (HTTP) → Parse → IF score ≥ 70 → Slack → Respond

I don't use a vendor-specific AI node. The LLM call is a plain HTTP Request to /chat/completions, so it works with OpenAI, Groq, OpenRouter, or local Ollama. Just change baseUrl.

The prompt that makes it reliable

You are a B2B sales analyst. Score inbound leads 0-100 for fit and intent using BANT.
Return JSON: {score, tier, summary, reasons[], next_step}

Add response_format: {type: "json_object"} and the IF node can branch on {{$json.result.score}} without breaking.

Try it

curl -X POST http://localhost:5678/webhook-test/lead-qualifier -H 'Content-Type: application/json' \
  -d '{"name":"Priya","company":"Acme SaaS","message":"Need an onboarding bot, budget $2k, this month"}'

Response: {"score":82,"tier":"hot","next_step":"Book a call this week..."}, and a Slack ping.

Get the workflow

The JSON is free on GitHub: https://github.com/arkintof/n8n-ai-agent-workflows

Want more like it (support agent, invoice/GST extractor, competitor digest, resume screener)? The repo README lists them: https://github.com/arkintof/n8n-ai-agent-workflows