Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application.
Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less.
Qrvey’s multi-tenant data lake includes:
Qrvey’s embedded visualizations support everything from: - Standard dashboards and templates - Self-service reporting - User-level personalization - Individual dataset creation - Data-driven workflow automation
Qrvey delivers this as a self-hosted package for cloud environments. This offers the best security as your data never leaves your environment while offering a better analytics experience to users.
The result: Less time and money on analytics.
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Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies
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Qrvey takes a different approach to embedded analytics. Instead of focusing almost completely on the front end, we know that any analytics function starts with data.
Qrvey includes a full-featured data lake powered by Elasticsearch, not a basic relational caching layer. Furthermore, by including a data lake, the cost to scale out is much less than traditional data warehouses.
For the user-facing components of the platform, Qrvey offers more embedded components and APIs to personalize the experience beyond static dashboards. Qrvey offers:
All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple.
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Customers choose Qrvey for the following reasons:
Based on our record, Google ARCore should be more popular than Qrvey. It has been mentiond 8 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Since you're on AWS already, check out https://qrvey.com. Source: 6 months ago
I don't know houw you would do it on ios but you should be able to do it on android if the phone supports it with.this library from google: https://developers.google.com/ar. Source: about 1 year ago
If you have any control on the choice of the source/webcam, I'd recommend using a camera that can sense depth from the start (lidar cameras, like Intel RealSense if you are building something like a commercial robot; or a consumer device with lidar capabilities like iPad Pros since 2020, because they come with SDKs to do what you want from the start. E.g. https://developer.apple.com/augmented-reality/arkit/ or... Source: about 2 years ago
You guys are right that Unity doesn't support building for arm64 Linux. It looks like the op could potentially install Android on the Raspberry Pi, which may allow them to run Android APKs built with Unity. However, AR Core is needed in order for Unity's AR functionality to work, and I suspect it would take additional work to get AR Core working on the Pi with an external camera and gyroscope. Source: over 2 years ago
If the phone doesn't support ARCore, then you would have to implement all of the world / surface detection yourself inside your application code, which is very difficult problem to solve. Source: over 2 years ago
If you're looking to build a more advanced application, there are plenty of useful resources for all major technologies. For mobile apps, the best places to get started are docs for Google ARCore and Apple ARKit. Both platforms work with popular gaming engines like Unity and Unreal Engine. - Source: dev.to / over 2 years ago
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Vuforia SDK - Vuforia is a vision-based augmented reality software platform.
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ARToolKit - The world's most widely used tracking library for augmented reality.