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Scriptover – An AI Tool to Help Vets Focus on Patients, Not Paperwork

Hacker News

Scriptover – An AI Tool to Help Vets Focus on Patients, Not Paperwork

Hey HN, I’ve been working on Scriptover, a multimodal AI assistant that helps veterinarians create SOAP notes (Subjective, Objective, Assessment, Plan) from real client conversations, images, and lab data. The idea came from my brother, a hospital director in California, who was spending hours each night writing notes after long days at the clinic. I wanted to see if AI could help vets reclaim that time while keeping medical reasoning accurate and transparent. Scriptover listens, interprets, and structures cases into clear, editable records — helping clinicians focus more on patients and less on paperwork. You can try it here → https://www.scriptover.com Happy to hear thoughts or feedback from anyone building applied AI or working on healthcare workflow tools. Cheers, Iman

Visit product View on Hacker NewsOct 25, 2025

Actual performance

2points

Did not reach leaderboard

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

64%64% 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 HuntUnlikely to reach the leaderboard · Strong signals: notes · Missing: mac, agents, macos

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

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

37%37% predicted probability of success on TrustMRR, 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

33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

25%25% 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

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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