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Atom, find grants based on your research interests

Hacker News

Atom, find grants based on your research interests

Hi HN, I've built a grant discovery tool to help researchers speed up the grant application process. You can try out the grant search engine without signing up but for the personalized email newsletter but you will have to sign up and create a profile with your research interests. Please let us know if you have any feedback :) Background: My co-founder and I come from research backgrounds and one of the most common complaints we heard is how much time PI's spend finding and applying for funding (up to 50% of a researchers time) It currently takes 2-3 weeks to find the right grant to apply to. The current solutions are either navigating fragmented data sources, relying on govtech UX (looking at you grants.gov), or having a research administrator conduct a dedicated search for you. However, not every researcher has the luxury of a dedicated admin team. Solution: So we decided to build an automated service which did the work of a pre-award research admin team. For our MVP we built a recommendation engine that parses natural language, i.e. the researchers biography or research interests, and instantly finds the most suitable grants and delivers the suggestions by email. We've since fleshed this out into a google style search dashboard where you can save grants for future reference and have plans to assist putting these huge proposals together. Let us know if you have any feedback, we're constantly iterating and open to suggestions of improvements that can be made to the onboarding.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% 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: google, new, email · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · 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
48%48% 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 · Strong signals: personal, google · Missing: mobile apps, ios, entrepreneurs
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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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