Shaped
Everything You Need to Build Retrieval and Ranking Systems
Description:
Shaped is a cloud-based platform that provides APIs and tools for building and deploying ranking systems. It offers a variety of features to help developers quickly and easily create and manage ranking models, including a multi-connector SQL interface, a real-time feature store, and a library of pre-built models. Shaped is designed to be scalable, cost-efficient, and easy to use, making it a great option for businesses of all sizes.
For Tasks:
For Jobs:
Features
- Easy-to-use APIs
- Powered by PyTorch
- Instant deployment
- Declarative SQL APIs
- Handles transforms in real-time
- No manual work for you
Advantages
- Double your engagement
- Increase conversions by 20%
- Improve retention by 30%
- Easy to integrate
- Cost efficient
- Scalable
Disadvantages
- May require some technical expertise to use effectively
- Pricing may not be suitable for all businesses
- Limited customization options for advanced users
Frequently Asked Questions
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Q:How long will it take to integrate?
A:The integration process is quick. You can connect your data to Shaped in minutes, train your first model in hours, and fully integrate into your app in days. -
Q:How is Shaped different to Algolia, AWS Personalize...?
A:Shaped uses state-of-the-art AI technologies like transformers and Large Language Models (LLMs) to make complex data types, including text, images, and video, usable for ranking systems. Using all types of your data significantly improves ranking performance. Algolia and AWS Personalize don't support unstructured data understanding. -
Q:Can I use Shaped for multiple ranking use-cases?
A:Certainly! Shaped is designed to be used for all of your ranking use-cases. Typically the companies we work with deploy dozens. Once your data is connected to Shaped creating additional ranking models is easy. -
Q:How much data do I need?
A:There is no minimum amount of data required. Collecting interactions, for example clicks, views and or impressions is the only requirement. -
Q:Why shouldn’t I build this in-house?
A:The high cost of hiring multiple machine-learning engineers, the long time required to build and the on-going full-time maintenance required. We handle scalability and reliability without the worries. Shaped can take you from 0 to 1 in a few days at a fraction of the cost.
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