Most n8n examples online are trivial: connect Gmail to Slack, notify a channel when a row is added to a sheet. Useful for learning the tool, useless for understanding what it can do in a real business. Here are 8 automations we've actually built and deployed for clients.
1. Invoice reconciliation pipeline
What it does: ingests PDF invoices from email attachments, extracts structured data with Claude Vision, matches each invoice against open POs in a PostgreSQL database, auto-approves matches above 98% confidence, and sends a Telegram alert for exceptions with the discrepancy highlighted.
Details:
Trigger: email received with PDF attachment
Tools connected: Gmail, Claude API, PostgreSQL, Telegram
Outcome: 97%+ invoices processed without human involvement, monthly close time cut from 5 days to 1
2. Lead enrichment and qualification
What it does: when a form is submitted, the workflow fetches company data from Apollo, passes the enriched record to Claude to score ICP fit (1-5) with reasoning, routes high-scoring leads to a specific rep in the CRM with a Slack notification, and drops low-scoring leads into an automated nurture sequence.
Details:
Trigger: webhook from website form
Tools connected: Apollo, Claude API, HubSpot, Slack
Outcome: rep research time cut from 2+ hours/day to 20 minutes
3. Production reporting bot
What it does: field operators submit production numbers via Telegram throughout the day. n8n aggregates all inputs, calculates totals and variances against targets, Claude formats a plain-English daily summary, and leadership receives the report in Telegram each evening without anyone compiling it manually.
Details:
Trigger: scheduled (6pm daily) + Telegram message listener
Tools connected: Telegram Bot API, PostgreSQL, Claude API
Outcome: daily reporting shift from 45 minutes of manual aggregation to zero
4. WhatsApp customer support
What it does: incoming WhatsApp messages are classified by Claude into categories (order status, returns, product question, complaint, other). FAQ-type queries are answered directly from a knowledge base. Complaints and complex queries are routed to a human with a summary. All interactions are logged to the CRM with classification and resolution status.
Details:
Trigger: incoming WhatsApp message via Business API webhook
Tools connected: WhatsApp Business API, Claude API, HubSpot
Outcome: 75% of queries handled without human, response time under 2 minutes 24/7
5. Competitor monitoring
What it does: every Monday at 7am, n8n scrapes the pricing pages and feature pages of 5 competitor sites. Claude compares the current content to the version from last week and writes a brief highlighting what changed - new pricing, removed features, new product announcements. The brief lands in Slack before the team starts their week.
Details:
Trigger: weekly cron (Monday 7am)
Tools connected: HTTP scraper, PostgreSQL (stores previous versions), Claude API, Slack
Outcome: competitive changes caught immediately instead of weeks later
6. Contract expiry monitoring
What it does: a daily job queries a PostgreSQL contracts table for contracts expiring in the next 30, 60, and 90 days. For each one, Claude drafts a personalized renewal outreach email using the contract details. Drafts go into a review queue in Notion. The sales rep reads and approves or edits, then sends. No contract slips through unrenewed.
Details:
Trigger: scheduled daily
Tools connected: PostgreSQL, Claude API, Notion
Outcome: contract renewal rate increased, manual tracking spreadsheet eliminated
7. E-commerce abandoned cart recovery
What it does: when a Shopify checkout is abandoned, n8n waits 2 hours, then passes the cart details (products, prices, customer history) to Claude. Claude writes a personalized recovery email referencing what was left in the cart. The email is sent via Klaviyo from the brand's sending domain. Not a template - a generated email specific to that cart.
Details:
Trigger: Shopify webhook (checkout abandoned)
Tools connected: Shopify, Claude API, Klaviyo
Outcome: recovery rate 2x compared to previous template-based sequence
8. Supplier reorder automation
What it does: a daily job checks inventory levels for each SKU in a Google Sheet. When a SKU drops below the reorder threshold, Claude drafts a purchase order email to the supplier including SKU, quantity needed, and delivery address. The draft goes to a Telegram approval queue. One tap to send. All orders are logged to a tracking sheet.
Details:
Trigger: scheduled daily
Tools connected: Google Sheets, Claude API, Gmail, Telegram
Outcome: stockouts eliminated, reorder process cut from 1 hour to 5 minutes per week
Getting started with n8n
Verified September 2026 on n8n's own pricing page: cloud Starter is 20 EUR/month for 2,500 workflow executions, Pro is 50 EUR for 10,000, Business is 667 EUR for 40,000. Note the unit - n8n bills per workflow execution regardless of how many steps are inside it, which is why deep workflows are far cheaper here than on platforms that bill per module. Self-hosted community edition costs nothing to licence and runs on a VPS for $5-50/month with no execution limit, in exchange for owning uptime, updates and backups yourself.
What these cost to build
Rough bands for the eight above, so the list is useful rather than aspirational. A scheduled report or a reorder flow like numbers 3 and 8 is one to three days and $1,200-2,500. A qualification or support flow with a model doing judgment, numbers 2 and 4, is $2,500-6,000. The document pipeline in number 1 is $4,000-8,000, mostly because of the matching logic and the ERP integration rather than the extraction.
The part these examples hide
Each description above is the happy path, and the happy path is roughly a fifth of the work. What separates a demo from something you can leave running is the unglamorous half: what happens when a third-party API returns an error halfway through, whether a retried webhook can process the same record twice, whether a failure is loud or silent, and who finds out.
That is also where the price difference between quotes comes from. If two builders quote the same flow and one is half the price, the difference is almost always error handling, and you will meet it later.
Getting started
The learning curve is real: plan a day or two with the interface before building anything production. Start with a flow where a silent failure would be merely annoying rather than expensive, and add the error handling from the first build rather than after the first incident.
Want one of these automations built for your business? Book a free audit call and we'll scope exactly what it takes.
Originally published at 2pizza.team. We build AI and automation systems for small teams - fixed price, two to six weeks. See the work.
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