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We have recently launched our new product REPODS ( https://repods.io ) and would like to hear your feedback! REPODS is an online data warehouse service for managing and analyzing data histories in data pods. Data can be imported via various interfaces, which facilitate the integration of all data (ERP, CRM, etc.). IoT devices can also stream data directly to a data pod for cross-analysis with all other data warehouse data. Data Pods are compact data warehouses equipped with storage and computing resources and all necessary tools. Each pod runs on its own infrastructure for maximum security and stable performance. The infrastructure can be flexibly scaled within a few seconds. REPODS is the ideal solution for small or medium-sized companies, as well as departments of large companies that are looking for a modern and lightweight industry 4.0 data warehouse solution. Already starting from 0€ monthly you can create your own Pod. Both flat rates with pre-defined resources and a freely configurable pay-per-use model are offered.

Visit product View on Hacker NewsMay 24, 2018

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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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61%61% 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: month, monthly · Missing: mobile apps, ios, personal

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

Product HuntUnlikely to reach the leaderboard · Strong signals: model, new · Missing: mac, agents, macos

39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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