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Scout AI (Neo '24) – A sales prospecting tool that works

Hacker News

Scout AI (Neo '24) – A sales prospecting tool that works

Hi HN. We're Christian and Daniel, cofounders of Scout AI ( https://scoutnow.ai ) which is backed by Neo. We were tired of wasting time on bulky sales tools, so we built one that is lightweight and actually works in terms of generating relevant leads for your business. Here's an intro / demo: https://www.youtube.com/watch?v=u8m1tWDkdrY Scout understands your business and target customer profile, and then works 24/7 to automatically source and qualify leads based on your exact criteria. It can check things like: - Healthcare: make sure the practice has at least 5 doctors/providers - B2B SaaS: focus on startups that are Series A or B and raised more than 12 months ago - Local businesses: make sure they have at least 10 locations across 2 or more states Our goal is to help startups and SMBs compete with large players by leveling the prospecting playing field, so that you don't need an entire team of "GTM engineers". Last week, Scout qualified 5K leads in under 24 hours for one healthcare SaaS founder, and then he booked 3 discovery calls in one day. We'd appreciate feedback, especially from folks who are running a successful top-of-funnel using other tools, and we are here to answer any questions. Happy prospecting .

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
29%29% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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