Open-source Gmail CLI for AI powered mailmerge and cold outreach

Hacker News

Hey HN! My cofounder and I are both technical and we found that while cold email is effective, tools like Apollo were meant more for full time BDRs. We decided to write a script that does our cold email outreach for us and figured we'd share with the HN community! Best part - we use LLMs for "fuzzy" merging so you don't need to worry about exact template matching. If you've also felt this pain, check it out!

Visit product View on Hacker NewsMay 23, 2024

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, open · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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