AI sales agents that find high-intent LinkedIn buyers and book meetings automatically
Find Reddit posts where people are asking for what you built, with draft answers ready
Stage
Not given
Startup
Founded
Not given
Not given
Based in
GB
JP
Pricing model
Paid
Freemium
Pricing
Starter: $149/month per user with 5,000 credits and 2 Signal Agents 24/7. Growth: $449/month per user (Popular) with 25,000 credits and up to 10 Signal Agents 24/7. Enterprise: Custom pricing. All plans include 7-day free trial with no card required.
Trial: $9 USD for 3 days (then $39/month); Monthly: $39 USD per month; 3 months: $79 USD for 3 months (then $29/month)
Key features
Signal-led warm buyer identification that monitors engagement across niche, competitors, and influencers
Hyper-personalized outreach with contextual openers built from exact engagement signals
ICP matching and niche-based learning
LinkedIn-safe pacing and automated follow-ups
24/7 signal agents monitoring buyer activity
Unibox integration with intent classification and auto-draft
CRM and MCP integration with Claude and OpenAI
Daily Reddit post discovery up to 10 posts per morning
Draft replies pre-written for each post
Post scoring based on fit, pain, ask, and exposure
Search terms automatically generated from product URL
Subreddit rules marked (Plain only vs Link OK)
Posts ranked by current engagement (comments per hour)
Reply Studio for editing drafts and tracking posts answered
One-click cancellation from account anytime
What makes it different
2-5x higher positive reply rates through signal-led personalization versus cold outreach
30-50% more meetings booked with less manual prospecting time
85% reduction in prospecting research time with automated signal detection
Intent-based lead queuing that prioritizes hot prospects over chronological order
Never posts anything for you - full control stays with the user
Searches Reddit overnight and delivers list each morning at 7:00
Automatically builds search terms from your product page
Ranks posts by real-time engagement, not popularity scores