Shaped vs. AWS Personalize

Daniel Camilleri
September 9, 2022
 min read

How to compare Shaped with AWS Personalize

Before I breakdown the differences let me explain why we exist in the market today. For Amazon, AWS Personalize is an afterthought to their core business. Whereas for Shaped, recommendations, ranking and discovery is our core specialty. We exist to solve the problems inherent in products like AWS Personalize and make state-of-the-art machine learning accessible to all companies.

The top three differences

1. Shaped connects directly to all of your existing data sources

Connecting directly to your data makes set-up with Shaped easy and maintenance almost non-existent. Most companies have data stored in a few places. For example, users and items in BigQuery and interaction data in Segment. We can connect directly to multiple sources where your data is stored. AWS Personalize requires you to coerce your data, push and store it on AWS infra. These extra steps require more maintenance time and effort for your engineers.

Examples of data connectors that Shaped connects directly to

2. Companies using Shaped get white-glove treatment

Our team of machine-learning engineers from FAANG will set up your initial models and discuss your business objectives with you. This will save you hours during setup and potentially months of experimentation time. We’ll explain how it works, what features are important and share performance insights with you regularly. While machine-learning is complicated, we’re not a black box. It’s extremely important to us that the results are interpretable and you understand how your models work.

We take you through step-by-step exactly how the system works

3. Technology designed to solve the cold start problem

We use state-of-the-art machine-learning techniques and pre-train our models so you don’t need much data to get started. In addition, we support all data types to build features even if they're unstructured (image, text, graph etc.). This gives our models better signals and helps deal with the cold start problem. Shaped reduces the performance gap between FAANG companies with 100s of machine-learning engineers and those with few or none.

Shaped uses pre-trained models to build data features that deal with the cold start problem

Shaped vs. AWS Personalize

Ease of use and maintenance


What about pricing?

AWS is known for their confusing pricing and their Personalize product is no exception. You’ll need a spreadsheet to model an hourly estimate and then forecast your monthly cost based on peaks and troughs in usage. With AWS you need to monitor your pricing closely, like a hawk. There are always gotcha moments where you find out you’ve been stung with hundreds or thousands extra on your invoice 🤬

At Shaped we want to keep things simple and focus on the things that matter so we do flat-fee monthly pricing based on forecasted usage and compute requirements. Once we’ve discussed your users/items/events we can provide a number to get started.

Thanks for reading, if you have any questions or want to discuss personalization for your product feel free to reach out to

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