I built a app for my mother

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Pasting the Why url contents here: Borivali railway station had 6 platforms in this manner physically. 1 2 3 4 5 6 Then we got platform 7 and 8 which made it like this. 8 7 1 2 3 4 5 6 So a person staying in Borivali East who would board a train going to platform 8 or platform 7 will have to walk the full length of 7 or 8 then climb steps or use subway all the way from 1 to 6. Certain people liked platform 7 and 8 as this was closer to catching a bus or rick or just close to their home. Either way it was both good and bad. The problem was the railway folks started announcing this when the train arrives at Malad or Kandivali, two stations before Borivali, even though the schedule is really fixed and does not change frequently. My mother travels everyday from Borivali-Dadar-Borivali for her job. It would be very irritating for her to get down at Malad or Kandivali, if a particular train would go to platform 7 or 8, as she has health issues esp. knee joints. We are dealing with rush to first board a train and then a rush to get down one station before your destination, too much to ask for from a women approaching 50 in my opinion. So I built this for her. I built a mobile app for her nokia phone. I coded a quick html/js page which I transferred on her phone via usb cable and then just opened it in the browser. It does not need internet. Now she's using it and suggested that I should put this up as few more people might find it useful. So here it is Borivali platform 7 and 8 app. I hope you find it useful.

Visit product View on Hacker NewsFeb 26, 2012

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Product HuntOn track for Day 1 leaderboard · Strong signals: physical, using, code · Missing: mac, agents, macos

67%67% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting

61%61% 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: io · Missing: https docs, excited, just released

50%50% 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 · Strong signals: platform · Missing: plus, intuitive, reviews

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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.

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