Developer platform for creating human-like conversational AI apps

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Hey all, I wanted to share with you this cool platform for developers that lets you build conversational AI apps in a matter of hours. Even a non-developer can build a demo app in less than 2 hours. Why is Dasha unique? * We have our own intuitive programming language - DashaScript. It's an event-driven language intended to describe a conversation script. * We created Dasha Studio, an extension to VSCode. You use the studio to create your conversational script, it gives you syntax analysis and highlight. There's also a visual graph editor. * Dasha CLI that lets you log in and get your API key that you can then use to execute conversational AI apps, and get diagnostic information about current usage, queues, and limits on Dasha Cloud Platform side. * Dasha Cloud provides conversational AI as a service, which means that you don’t need to be a machine learning engineer to use machine learning when building Dasha conversational apps. * We use GRPC for communication between SDK and the Dasha Cloud (more on that here https://dasha.ai/en-us/blog/conversational-application) What apps can you build? To illustrate how to build a conversational app and show its capabilities, here's an audio demo + tutorial on how to create a conversational AI app that automates money transfers (and more): https://dasha.ai/en-us/blog/money-transfer-automation You can create apps for free, so give it a try: https://dasha.ai/en-us/ (just click on "API key" button and we'll provide you one so you can start building) Also, we're hiring a DevRel, so if you are one or know one, apply or reach out! https://www.notion.so/dashaai/Dasha-is-hiring-6f2156ae251e4e9b94c841fff4fcd976

Visit product View on Hacker NewsAug 27, 2021

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apps, visual · Missing: agents, macos, agent

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

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.

TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% 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

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · 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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