Stop paying $300/mo: 5 n8n workflows realtors run for $24

$300 a month. That’s the median SaaS bill for a working US realtor in 2026. CRM, lead routing, drip emails, calendar booking, voice AI, the works. Most of it doesn’t even talk to itself.

The agents paying $24 a month for the same outcomes have one thing in common. They built it in n8n, an open-source workflow tool. They route leads, qualify with AI, run voice agents, and ship listing descriptions through one tool that costs less than a Lofty seat.

We pulled the 5 workflows that come back the most in r/RealEstateTechnology threads, n8n community templates, and public GitHub repos. Here’s what each one does, what it costs, and where it breaks.

Why realtors are jumping to n8n

Three reasons keep showing up in Reddit threads and on community Slack channels.

It’s cheaper than the AI assistant SaaS pile. Most “all-in-one realtor AI platforms” charge $179-499/mo. n8n Cloud is $24. Self-hosted n8n runs $5/mo on a small VPS. You pay only for the API calls (OpenAI, Claude, Twilio).

It connects what doesn’t connect. Your MLS doesn’t talk to your CRM. Your CRM doesn’t talk to your voice AI. n8n is the duct tape. It has 350+ integrations and can call any REST API, so it covers the gaps.

Other realtors have already built it. A wholesaler on r/RealEstateTechnology described his stack: “I built it using JSON and n8n. I’ll see about getting a Github repo put together so you can have the files.” That’s the pattern. Agents share workflow JSON files like recipes.

A second builder put it bluntly: “Make.com, n8n are best platforms that won’t need extensive programming expertise.” You don’t need to code. You drag nodes, connect lines, and click “Run”.

Workflow 1: Lead intake with AI qualification

The problem. A lead fills out your IDX form or Zillow contact button. The lead lands in your CRM as just a name and email. You spend 3-5 min figuring out if it’s a real buyer, a tire-kicker, or a vendor pitching. Multiply by 2-4 inbound leads a day for an average solo agent (more if you’re paying for Zillow Premier or running ads).

The workflow (5 nodes):

1. Webhook trigger. Your lead form posts to it.
2. OpenAI / Claude node. Sends the lead’s name + email + message to GPT-4-mini with a strict scoring prompt: hot / warm / cold + reason.
3. IF node. Branches on the score.
4. HTTP Request to FollowUpBoss API. Creates the contact with tags.
5. Twilio SMS. Texts you only if the score is “hot”.

Sample scoring prompt (drop this into the OpenAI node):

You are a real estate lead qualifier. Given the inputs below, return JSON:
{ "score": "hot" | "warm" | "cold", "reason": "<15 words" }

HOT = explicit buying intent + timeline ≤ 90 days + specific area or price
WARM = browsing serious, no timeline, or financing question
COLD = vendors, surveys, vague "I'm thinking about real estate"

Inputs:
Name: {{ $json.name }}
Email: {{ $json.email }}
Message: {{ $json.message }}
Source: {{ $json.source }}

What it costs. ~$0.0003 per lead with GPT-4-mini. 200 leads/month = $0.06.

Time saved. 10-20 minutes a day at typical solo-agent volume (2-4 leads/day). About 1-2 hours/week. Higher if you run paid Zillow / Facebook lead ads (5+ leads/day pushes it to 3-4 hrs/week).

Where it breaks. GPT-4-mini occasionally mislabels investor leads as cold. The fix builders use is a keyword fallback that flags “cash”, “1031”, or “investor” as warm regardless of the AI score.

Workflow 2: Daily MLS digest for buyer clients

The problem. Buyers ghost you between listings. You forget to send updates. By the time you remember, they’ve found something on Zillow without you.

The workflow (4 nodes):

1. Cron trigger. Every day at 7 AM.
2. HTTP Request to your MLS RETS / Spark API. Pulls last 24h listings matching saved searches.
3. OpenAI node per listing. Generates a 2-sentence highlight tuned to the buyer’s preferences.
4. Gmail / SendGrid send. One personalized email per buyer.

The personalization prompt is what makes this work. Pulling raw MLS data and dumping it into an email looks like spam. A short Claude or GPT pass that mentions “you mentioned you wanted a finished basement, and this one has it” turns it into a useful note.

What it costs. $5-10/mo in API calls if you have 20-50 active buyer searches.

Time saved. 30-60 min/day if you have 15-30 active buyer searches. The replaced workflow isn’t “manually scanning the MLS daily” (most realtors already have auto-alerts set up), it’s the personalization layer + skipping the dud listings before forwarding. About 2-4 hours/week.

Where it breaks. MLS rate limits. RETS feeds throttle hard. You may need to cache listings in a Postgres node.

Workflow 3: Vapi voice agent + n8n routing

The problem. You miss after-hours calls. Or you take them and the lead is unqualified. Either way, leaks.

The workflow (Vapi + n8n combo, what most realtor-builders are converging on):

1. Vapi answers the call with a voice assistant trained on your service area + price ranges + qualification questions.
2. Webhook from Vapi sends the transcript + structured data to n8n.
3. n8n routes based on price band: solo agent for < $500k, partner for $500k-1M, broker for $1M+.
4. Calendar API. Proposes 3 slots based on routed agent’s availability.
5. CRM API. Drops transcript + qualification data into the contact record.

A working builder described their architecture this way: “all of the backend processing is custom code, the calling itself is handled by VAPI, and the function calls are performed using n8n.” That’s the canonical pattern.

What it costs. Vapi: $0.05-0.20/min depending on the model. A 5-min qualification call = $0.25-$1. At 50 calls/month, you’re at $12-50/mo. Plus n8n Cloud at $24/mo.

Time saved. Depends heavily on inbound call volume. Solo agents reporting 5-15 calls/week back to 1-2 hours/week. Teams with 50+ inbound calls/week and after-hours leakage report 3-5 hours/week recovered.

Where it breaks. Latency. Cascaded systems (speech-to-text, LLM, text-to-speech) feel sluggish. Some builders are moving to Gemini’s native audio model for end-to-end flow. Worth watching.

A polarizing note. Voice AI annoys some agents. “I receive calls from ‘AI Assistants’. Hot Take I hang up immediately.” is the top comment from r/realtors with 76 upvotes. The trick is using voice AI for inbound, not cold outbound. Inbound = the lead expects to talk to a person, the AI bridges to one. Outbound = spam.

Workflow 4: Listing description generator that doesn’t sound like ChatGPT

The problem. Buyers and other agents have learned to spot ChatGPT listings. From a r/RealEstate thread that hit 41 upvotes:

“Every single listing I look at is ‘a rare gem’ in ‘the desirable neighborhood’ of xyz. Pro tip: if every neighborhood is desirable, none of them are. It’s a drinking game at this point.”

If you write straight ChatGPT output, buyers tune out and your DOM goes up.

The workflow (3 nodes + a quality gate):

1. Form trigger. You paste the property data: bedrooms, bathrooms, lot size, 5 stand-out features, the buyer profile.
2. OpenAI / Claude node with a banned-words system prompt.
3. IF node. Checks the output for any banned word. If found, regenerates.
4. Google Docs node. Drops the output into a shared doc for review.

The system prompt is the leverage:

Write a 150-word real estate listing description.
RULES:
- Never use: "rare gem", "desirable neighborhood", "boasts", "nestled",
  "chef's kitchen", "must-see", "won't last", "luxurious", "stunning",
  "dream home", "oasis", "pristine", "spacious"
- Sentences max 18 words
- Include 3 specific numbers (square feet, year built, distance to schools)
- Lead with the strongest concrete fact, not an adjective
- End with one specific call to action

Property:
{{ $json.facts }}

Buyer profile:
{{ $json.buyer_profile }}

The IF node is the safety net. Even with the rules, GPT slips. The IF node greps the output for banned words and re-runs if it finds any.

What it costs. $0.001 per listing with GPT-4-mini. 30 listings/year = $0.03.

Time saved. 15-20 minutes per listing description. For a 30-listing-a-year agent, that’s ~9 hours saved annually, plus a measurable lift in click-through.

Workflow 5: Post-close review automation

The problem. Reviews are the cheapest backlinks and trust signals you’ll ever get. But asking for them is awkward and you forget.

The workflow (5 nodes, runs in the background forever):

1. CRM webhook. Fires when a deal status changes to “closed”.
2. Wait node. 14 days.
3. Claude node. Generates a personalized review request based on what you logged about the client (kid’s names, the inspection drama, the appraisal save).
4. SendGrid / Gmail node. Sends the request.
5. Form trigger for the response. If 5★, auto-redirects to your Google Business Profile review form. If < 5★, drops into a private Slack channel for follow-up.

The 14-day wait matters. Day-of-close is too soon (clients are exhausted). Day-30+ is too late (the gratitude wears off).

What it costs. Pennies. $1-3/mo in API calls.

Time saved. 10-15 minutes per closed deal vs writing each request manually (most agents send a quick generic email). For a 40-deal-a-year agent, that’s 7-10 hours saved annually (~10 min/week sustained). The bigger win is review volume: builders report 2-3x more reviews when the ask is personalized and timed at day 14, though it varies a lot by client base.

Cost and time summary

Total stack at full deploy: ~$75/mo in API + n8n Cloud. Total time saved: 5-9 hours/week sustained at average volume, plus the cyclical wins on listing batches and closed deals. That’s not “save half your week” territory. It’s “claim back one full evening plus a chunk of your weekend” territory, which is honest and still worth the build effort. Compare to one all-in-one platform charging $299/mo for less control.

Where this stack breaks (the honest part)

1. n8n itself has a learning curve. First 6-12 hours feel like punching air. After that, every new workflow takes 30-60 min. Don’t promise yourself you’ll save time on day 1.

2. API costs creep. Watch the OpenAI dashboard. Runaway loops in n8n are a known failure mode. Community threads describe overnight bills of $50-200 from a single misconfigured node. Set hard spending limits in your OpenAI / Anthropic dashboard before the first run.

3. Self-hosted n8n needs a sysadmin. A $5 VPS plus Docker isn’t free in time terms. If you’d rather not babysit a server, n8n Cloud at $24/mo is the right call. Skip the saving.

4. MLS terms of service. Some MLS providers ban scraping or third-party access. Read your access agreement. The legal risk lands on the agent, not the tool.

5. Voice AI is still uncanny. A solo realtor’s gut take from r/realtors: “I am getting similar AI recruiting calls and my production is hardly impressive. I hang up as well.” Use voice AI for inbound qualification, not cold outbound. The receiving end shapes the verdict.

Getting started: the 90-minute path

If you’ve never opened n8n, here’s the fastest first win:

1. Sign up for n8n Cloud ($24/mo, 14-day trial). Skip self-hosting for now.
2. Build Workflow 1 (lead routing). 90 min from cold start. Start with the templates linked in n8n’s marketplace.
3. Run it on real leads for 3 days. Don’t add a second workflow until #1 has been live a week.
4. Add Workflow 4 (listing descriptions). 30 min, instant ROI.
5. Skip Workflow 3 (Vapi) until the first two are stable. Voice AI is the deepest rabbit hole.

That’s the order we’d recommend. Don’t try to ship all 5 in a weekend.

We’re scheduling 14-day tests of each workflow starting in May 2026, on a real solo agent’s lead list (anonymized). Standalone reviews with the n8n JSON exports and screen-recording walkthroughs will follow as each test wraps. Subscribe to the newsletter or RSS to catch them.