EngageAI

AI converts post engagement into qualified prospects automatically. Analyzes comments for buying signals, responds in 60 seconds. Never miss LinkedIn leads.

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About EngageAI

What Inspired Me

Every single day, I was spending an hour manually copying and pasting DMs to people who commented on my LinkedIn posts asking for resources. That's 365 hours a year - literally nine work weeks of my life just... copying and pasting. My lead magnet posts work exactly as designed - people comment asking for guides, resources, and tools. But I was losing the leads I worked hard to generate because the follow-up process was entirely manual. When someone comments "MEDICAL" asking for my AI guide, they're a qualified prospect showing clear buying intent. But if I don't respond within hours, they lose interest and move on. I realized I was watching qualified leads slip away not because my content wasn't working, but because I couldn't scale my response process. I looked everywhere for a solution - there's ManyChat for Instagram comment automation, but absolutely nothing for LinkedIn comment-to-DM workflows. That's when I knew I had to build it myself.

What I Learned

The gap between generating leads and capturing leads is where most revenue dies.

My lead magnets were working perfectly - driving engagement and qualifying prospects. The breakdown happened in the manual follow-up phase. Even a few hours delay meant losing interested prospects.

I learned that LinkedIn automation isn't about being faster - it's about consistency. AI doesn't forget to follow up or get overwhelmed when 30 people comment asking for the same resource.

How I Built It

Pure no-code approach in 30 days:

  • Frontend: Bolt for rapid UI development
  • Backend: n8n workflows for automation logic
  • Authentication: PocketBase for user management
  • AI: Claude/GPT for comment analysis and intent detection
  • Database: PostgreSQL for user data and analytics
  • API: LinkedIn integration for posts and messaging

Key workflows built:

  1. Posts Monitor - Detects CTA keywords in new posts
  2. Comment Analyzer - AI analyzes every comment for buying signals and intent
  3. Response Engine - Sends personalized DMs while respecting LinkedIn's rate limits
  4. Human Oversight - Draft approval system for quality control

Challenges I Faced

1. LinkedIn Rate Limiting

LinkedIn has strict daily limits (15-20 connection requests, 100-150 messages). I built a sophisticated tracking system with user-configurable safety modes to prevent account warnings.

2. AI Accuracy

Early AI was marking any comment containing keywords as prospects. Had to build exact-match CTA detection and sentiment analysis to avoid false positives.

3. Human-Like Behavior

LinkedIn detects automation patterns. Implemented random delays (2-60 minutes), natural timing, and human approval workflows to maintain authenticity.

4. Multi-User Architecture

Started as a personal tool, had to redesign for multiple users with independent rate limiting and template management.

5. No-Code Limitations

Complex logic in n8n required creative workarounds. Built modular workflows that could handle edge cases without traditional programming.

What Makes It Special

This isn't another LinkedIn automation tool - it's warm engagement automation.

Instead of cold outreach to strangers, EngageAI converts people who are already interested in your content. It bridges the gap between successful lead generation and successful lead capture.

The vision: build a complete LinkedIn lead generation platform. Start with comment-to-DM automation, then expand to other LinkedIn automations that generate and capture leads at scale.

Built With

  • bolt
  • claude
  • cloudstation
  • linkedin
  • n8n
  • pocketbase
  • pocketbase-auth
  • postgresql
  • tailwind-css-|-backend:-n8n-workflows
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