6
Spent 6 months building a software to automate IG growth — finally feels like it’s clicking
r/SaaS
7/7/2025
Content Summary
A developer spent 6 months building AutoViral, a SaaS tool that repurposes old Android phones to automate Instagram/TikTok engagement through likes, shares, DMs and simulated human patterns. Key challenges included device management and UI development. The project survived through community feedback via Telegram/Discord groups. Current growth strategies involve scraping niche groups for targeted outreach using 40-phone farms and developing an LLM for automated responses. Revenue is at $50/mo with plans to scale through YouTube content and agency partnerships.
Opinion Analysis
Mainstream opinion supports community-driven development and infrastructure-first approach. The author emphasizes iterative improvements based on user feedback. Commenters stress device stability over growth, advocating for technical safeguards like watchdog daemons and randomized delays. Controversy exists around ethical implications of automated DM scraping. Some suggest focusing on agency-tier monetization while others warn about platform detection risks. Debates center on balancing automation authenticity with scalability.
SAAS TOOLS
| SaaS | URL | Category | Features/Notes |
|---|---|---|---|
| AutoViral | https://autoviralapp.com | Social Media Automation | Controls old Android devices, automates engagement (likes/shares/stories), DM funnels, simulates real patterns, workflow automation via n8n-style dashboard |
| Phantombuster | Not provided | Data Scraping | Quick profile pulls (mentioned in comments) |
| Apify | Not provided | Web Scraping | Bulk post stats (mentioned in comments) |
| Pulse for Reddit | Not provided | Monitoring | Flags new anti-bot techniques in niche subs (mentioned in comments) |
USER NEEDS
Pain Points:
- Managing device stability (bricked devices, script failures)
- Handling IG rate limits and bans
- Scaling infrastructure for growth
- User interface complexity
- Stress from continuous product iteration
Problems to Solve:
- Automating social media growth without constant manual effort
- Maintaining authentic engagement patterns
- Scaling outreach while avoiding platform detection
- Managing hardware reliability for automation farms
Potential Solutions:
- Implementing watchdog daemons for device health monitoring
- Adding randomized delays and staggered sleep blocks
- Offering done-for-you service plans for agencies
- Building community-driven feedback loops
- Developing AI (LLM) for automated DM responses
GROWTH FACTORS
Effective Strategies:
- Community-driven development via TG/Discord groups
- Infrastructure building for scalability
- Hybrid automation (auto-DM + manual follow-up)
Marketing & Acquisition:
- Niche targeting through TG/Discord group scraping
- YouTube content marketing with demos/results
- Collaborations with agencies/OFM systems/streamers
Monetization & Product:
- Transitioning from $50/mo to done-for-you agency plans
- Balancing automation with user control (dashboard visibility)
- Risk disclaimers for account safety
User Engagement:
- Direct user testing and feedback implementation
- Transparency in product updates
- Building trust through manual response phase before full automation