Automating Web-Based Onboarding Flows with n8n + Prompt Agents + Antidetect Browsers

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1

Hi everyone,

I recently tackled a challenge that many SaaS founders, growth teams, and even automation engineers face: scaling onboarding workflows on third-party platforms (e.g., signing up accounts, adjusting settings, verifying emails, connecting APIs).

Here’s how I managed to automate this flow end-to-end using:

  • n8n as the orchestration backbone
  • Prompt-based browser agents for human-like interaction
  • Hidemium as the antidetect browser layer

Let me break down what I learned.

:compass: Why This Use Case?

I needed to register multiple accounts across various SaaS tools (some for testing, others for growth marketing experiments). These platforms often implement:

  • CAPTCHA or Cloudflare checks
  • JavaScript-heavy forms
  • Email verification
  • Fingerprinting + IP-based restrictions

Traditional headless browsers kept failing, and writing Puppeteer scripts for every site was painful to maintain. So I explored a more modular approach.

:hammer: How the Stack Works

  1. n8n Workflow
  • Triggers from a Google Sheet row (account data input)
  • Pushes data via Webhook to my local controller
  1. Hidemium Browser Launch
  • Starts a fresh fingerprinted profile (unique IP, OS, fingerprint)
  • Each profile is isolated and logs into one account only
  1. Prompt Agent in Action
  • Receives instructions like:

“Open https://example-saascom, sign up using email X, solve CAPTCHA if asked, confirm in inbox.”

  • Agent interacts just like a real user: mouse movements, typing, clicking — all within the profile
  1. Email Verification Loop
  • Agent accesses the inbox via webmail or extension
  • Clicks confirmation link and completes onboarding
  1. Logging + Monitoring
  • Results are posted back to n8n
  • Errors logged, retries triggered, successful accounts archived

:light_bulb: What Makes This Approach Powerful

  • Resilient to UI changes: No need to re-code DOM selectors — just tweak the natural language prompt
  • Scalable: I run 20–30 onboarding flows in parallel across different profiles
  • Adaptive: AI agents handle “unexpected” UI elements better than brittle scripts
  • Private: Using antidetect profiles avoids IP blocks and reduces tracking

:test_tube: Real-Life Example

I onboarded 50+ accounts on an affiliate program platform for testing. Each flow included:

  • Unique name/email
  • Captcha resolution
  • Profile setup
  • Email confirmation
  • Setting API keys

The entire process was run overnight with less than 10% failure rate (mostly due to email latency). No bans, no IP blocks.

:warning: Limitations & Gotchas

  • Prompt agents aren’t perfect — some forms require manual fallback
  • Managing and syncing browser states can be tricky (timing is key)
  • Works best with a hybrid of automation and light human supervision at scale
1 Like
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I love this hybrid approach. Using n8n as the orchestrator makes so much sense. Have you benchmarked latency or throughput when scaling to, say, 100 accounts? I imagine browser startup time can be a bottleneck.

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Yeah, that’s a great point — startup time is definitely one of the main factors to watch.

From my testing:

  • A cold start for a Hidemium profile on my local machine is ~6–8 seconds, including fingerprint load + proxy handshake.

  • Once the profile is up, most of the “latency” comes from site-side delays (CAPTCHAs, email arrival, animations), not the automation stack itself.

  • At around 50 concurrent profiles, my throughput bottleneck actually shifted from CPU to network — the proxies and mail servers became the limiting factor.

For 100+ accounts, I usually:

  1. Batch in waves (e.g., 20–25 at a time) to avoid overwhelming resources.

  2. Reuse warmed profiles for sequential tasks instead of tearing them down each time.

  3. Use async task handling in n8n so browser startup overlaps with other workflows.

If you’re running cloud or distributed nodes, you can push that number higher, but on a single local rig, smart batching is the most reliable.