“Marketing Automation Tools for Amazon Sellers”
Founded by Leo Sgovio (Toronto). Bootstrapped. “We don’t really use anymore” — Michael Bitler
1–10
Employees
<$5M
Revenue
Zero
Public Reviews
“Don’t
use”
Current Status
Reduce 90% of manual customer service tasks for Amazon sellers through marketing automation.
Leo Sgovio — 13+ years digital marketing, A9 algorithm expert. Based in Toronto, Canada.
| Team | 1-10 employees |
| Revenue | <$5M |
| Funding | Bootstrapped |
| Reviews | Zero on any platform |
| Tier | Price |
|---|---|
| Free | $0 (limited features) |
| Trial | 7 days full access |
| Paid | Not publicly disclosed |
| Product Launch | Custom consultation |
Opaque pricing is a red flag for transparency
5-minute promotional campaign setup. Template-based, not generative.
Customer list creation from Amazon buyer data. Rule-based segmentation.
Purchase-history triggered, customer-chosen rewards system.
Pre-built templates on CSML-based decision trees. Not NLP/LLM.
Geotargeted QR codes linked to chatbot flows. Standard geo-IP lookup.
Done-with-you ranking + review strategy. Amazon TOS gray area.
| Feature | Reality |
|---|---|
| Chatbot flows | Template-driven decision trees, not NLP/LLM |
| ManyChat dependency | A layer on top of another platform |
| Audience segmentation | Rule-based (purchase history, events) |
| QR geotargeting | Standard geo-IP lookup |
| Campaign wizard | Template-based, not generative |
| API endpoints | get_order, send_payout — standard REST |
| Issue | Detail |
|---|---|
| Opaque pricing | Red flag for transparency |
| Tiny team | 1-10 employees — support and reliability risk |
| Zero reviews | Not listed on any review platform |
| Amazon TOS risk | Product launch + review generation in gray area |
| Not in roundups | Not listed in any major Amazon tool roundup |
| ManyChat dependency | Core functionality relies on external platform |
| No dev cadence | No visible development activity |
True Conversational AI
Persistent business context, not decision trees
Multi-Channel Coordination
Not just chatbot flows — voice, API, research, memory
Evidence-Gated Outputs
Not TOS-risky review generation — confidence-scored reasoning
Scalable Architecture
Not a 1-10 person team — distributed daemon mesh
Knowledge Graph Learns
Every customer interaction compounds intelligence