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Writing grant applications using AI

Hacker News

Writing grant applications using AI

For the past 6 years, I've run a digital mental health company in Kenya. I'm the sole grant writer, meaning that I have to prioritize (and deprioritize) which funding opportunities to go after. We created GrantAI to help small organizations win more grant funding through a grant writing tool. We have some initial traction and recurring subscription revenue. I'd love your feedback! (1) General feedback about product experience (beta.platform.grantai.co) (2) Feedback on our landing page (www.grantai.co) (3) How can we scale this? Thank you! Hope you all like it. - Alex

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, organizations · Missing: supports, reddit linkedin, podcasting
78%78% 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
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, recurring, subscription · Missing: arr, mrr, profit
26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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