relevance ai vs n8n: A Cost Controller's 6-Step TCO Checklist for AI SDR and Lead Gen Tools

If you've ever watched a “free plan” turn into a month of integration work, you know why I stopped starting with the sticker price. I'm a procurement manager at a mid-sized B2B analytics company. I've managed a six-figure sales-tech budget for the last six years, tracked every invoice in our procurement system, and sat through more vendor demos than I'd care to admit. When our RevOps team asked me to evaluate relevance-ai vs n8n for AI SDR, I did what I always do: built a TCO checklist.

Here's the checklist I use. It's six steps, not twenty. It won't make the decision for you, but it will show you where the money actually goes.

Step 1: Map the workflow before you map the tools

The fastest way to make a bad buying decision is to compare platforms before you understand the job. In our case, the job was: research accounts, verify email addresses, generate personalized first-line outreach, send cold email sequences, and route replies back to sales. That's not the same as a simple “when this happens, do that” automation.

n8n is a workflow automation platform. It can connect a lot of pieces, but each connection requires someone to build and maintain it. Relevance AI is a sales prospecting and engagement platform with AI SDR/BD agent workflows, data enrichment, and intent data included. I'm not saying one is better. I am saying they are not on the same TCO line unless your team has empty engineering hours to spend.

Before you look at pricing, write down your current outbound flow. Then mark which steps are manual, which are automated, and which are broken. That becomes your evaluation scorecard.

Step 2: Calculate TCO per qualified conversation, not per seat

When someone searches “relevance ai pricing free”, the real question is usually “can I get value before I commit a budget?” My answer: maybe, but free is a starting point, not a cost model.

Here's the TCO formula I use for these tools:

TCO = software subscription + data/enrichment/credits + API overages + setup/integration + internal team time + cleanup and redo costs.

If you only compare the license line, you'll miss the two biggest expenses: team time and bad data.

I checked n8n and Relevance AI pricing pages in January 2025. n8n had a free self-hosted Community edition and paid cloud plans. Relevance AI's page also had a free option, but free options usually come with limits on runs, contacts, or credits. Those limits matter when your AI SDR actually starts sending.

I'm not going to quote exact numbers because pricing pages change every few months. But I will say this: the platform with the lowest monthly price in January 2025 was not the lowest total cost in our Q3 review. Put another way: a “free” workflow that takes two hundred hours of engineering time is expensive.

Step 3: Test the email lookup tool, then test it again

Every AI SDR platform has an email lookup tool, so the feature itself tells you almost nothing. What matters is where the data comes from, how fresh it is, and what happens when an email bounces.

In our evaluation, one tool gave us a list of addresses that looked complete. We tested 50 sampled contacts against our existing CRM data, and a significant number had changed domains or were missing from the verification layer. That would have destroyed our sender reputation and made every subsequent email sequence worse.

What should you ask? At minimum: What is the verification/refresh cadence? What is the fallback when an address is invalid? Can you exclude certain domains? Is there an SLA for bounce rates? If the answer is “we don't really track that,” move the vendor one column to the right—toward the bad side.

Step 4: What should revenue operations teams evaluate in lead generation capabilities?

Feature checklists are dangerous because every vendor can borrow a feature name and put it on the pricing page. During our evaluation, I kept a separate list of capabilities that actually affect revenue operations:

• Source coverage: Which data sources feed the contact and intent data, and how does the tool dedupe them?
• Data freshness: When was the record last updated? Is the update automatic or only when you manually refresh it?
• Verification method: Does it check syntax, mailbox, domain, or all three?
• Enrichment depth: Is it just an email address, or does it include firmographics, technographics, and buyer intent signals?
• Integration quality: Does it sync cleanly to your CRM and marketing automation?
• Human oversight: Can your RevOps team review and edit the AI SDR's output before it sends at scale?

That last one matters more than people think. An AI SDR can generate messages around the clock, but if it's not grounded in your ICP and your messaging guidelines, you're just scaling bad outreach.

Step 5: Run a side-by-side test with the AI SDR on your own accounts

Don't buy an AI SDR based on a demo. Ask for a live test on a small list of your own accounts. Give the same ICP to Relevance AI, to an n8n workflow, and to whatever else you're comparing. Then look at the output with the same ruthless eye you'd use on a new rep's first email.

I want to see: account research that is not generic, subject lines that don't sound like a robot having a seizure, and replies that get routed to the right owner. And I want to see the tool's confidence score or source references. If it can't tell me where a fact came from, I can't trust it.

We tested maybe 12 AI SDR tools in the last 18 months—no, 13, I'm mixing it up with the old CRM comparison. The pattern was clear: the tools that let me set the playbook, review the output, and adjust the tone beat the ones that just looked impressive in a demo.

Step 6: Ask for a line-item quote and keep pushing

The most uncomfortable part of my job is asking vendors to explain their own pricing. I do it anyway. A line-item quote should include monthly plan, active contacts, AI credits, enrichment credits, API usage, onboarding, support tier, and migration help.

When one rep said “it's a free plan,” I asked what happens at 500 contacts. The answer: we have a paid plan for that. Fine. But I had to ask. Looking back, I should have asked about overage pricing in the first call—that “free setup” cost us more in internal time than it saved.

I once had two hours to sign off before a budget freeze. I rushed the vendor comparison and skipped the reference calls. In hindsight, I should have asked for 48 hours. It was the most expensive shortcut I've taken in this role.

If a vendor can't give you a sample invoice, assume there will be surprises. And if you're comparing relevance-ai vs n8n, remember that n8n's “build it yourself” path also has a line-item quote: your engineers' time. That's a line item that doesn't appear on any invoice, but it comes out of someone's capacity.

The Mistakes I Keep Seeing

After years of procurement work, these are the recurring ones:

Mistake 1: Comparing the annual license and forgetting the build. Low license cost often sits next to high setup or maintenance cost.

Mistake 2: Trusting “free” as a stress-free long-term option. Free plans are okay for testing. If you're building your entire RevOps motion around one, it becomes a job.

Mistake 3: Leaving RevOps team time out of the TCO. Your team is the most expensive resource in the room. A tool that saves $200 per month but costs 10 hours of maintenance is a bad trade.

So Which One Wins?

“Wins” is the wrong word. For our needs, Relevance AI's agent-native prospecting workflow and built-in data got us closer to a production-ready AI SDR with less internal assembly. n8n is a solid automation platform, and if you have engineering capacity and a custom stack, it can be the right fit. But that's a different TCO conversation.

Here's what I'd recommend: don't start with “which platform is cheaper.” Start with the workflow, run a small test, and calculate the total cost for a specific output—like a qualified reply. Then decide.