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Shaped

AI-native personalization platform for building ranking models and personalized experiences.

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Real Learning Machine Learning DESIGN ASSISTANT DEVELOPER TOOLS Developer Docs API Design Product recommendations Chat duet ai assistant ai flag generator AI Personalization Recommendations Ranking models Data Science Relevance engine E-commerce Social media Marketplaces Media platforms
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Verdict

A quick read before you dig into the full page.

Best if
You are machine learning engineers and need: Personalized discovery pages
Pick this when
AI-native personalization platform for building ranking models and personalized experiences

Overview

Shaped is an AI-native personalization platform that allows users to build powerful ranking models to understand the content their users are most likely to engage with or buy. This understanding can be used to create personalized discovery pages, feeds, recommendations, and marketing communication. Shaped helps teams rapidly experiment with AI search, recommendations, and personalization, offering a real-time, configurable relevance engine built for scale.

Shaped screenshot

Best for

Short scenarios where Shaped tends to shine.

  • Personalized discovery pages

    Best for Machine learning engineers

  • Customized feeds

    Best for Data scientists

  • AI-driven recommendations

    Best for Developers

  • Optimized marketing communication

    Best for Technical teams

  • Marketplace optimization

    Best for Product managers

  • Social media engagement

    Best for Machine learning engineers

  • Media platform personalization

    Best for Machine learning engineers

  • E-commerce conversion boosting

    Best for Machine learning engineers

Example outputs 1

Sample generations and before/after results for Shaped.

Shaped screenshot
Shaped screenshot

Access & connections

Where you can use Shaped.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Highlights

  • AI-powered search and recommendations
  • Real-time adaptability using behavioral signals
  • State-of-the-art model library
  • Highly customizable ranking and retrieval components
  • Explainable results with in-session analytics
  • Secure infrastructure with GDPR and SOC2 compliance

People also view

Tools that often show up alongside Shaped in collections and comparisons.

In the news

Launch coverage and community mentions for Shaped.

FAQ 8

What is Shaped?
Shaped is an AI-native personalization platform that allows users to build powerful ranking models to understand the content their users are most likely to engage with or buy. This understanding can be used to create personalized discovery pages, feeds, recommendations, and marketing communication. Shaped helps teams rapidly experiment with AI search, recommendations, and personalization, offering a real-time, configurable relevance engine built for scale.
How to use Shaped?
To use Shaped, connect your existing data sources, fine-tune LLMs and neural ranking models, and experiment with ranking and retrieval components. The platform integrates directly with data warehouses and supports SQL-based feature engineering, allowing technical teams to fully control and extend the system.
How long will it take to integrate?
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.
How is Shaped different to Algolia or AWS Personalize?
Shaped is built as a unified, AI-native platform designed for real-time, deeply customizable search and recommendation systems—purpose-built for modern data teams. It merges search and recommendations into a single system, uses transformer models and real-time learning loops, and integrates directly with data warehouses.
Can I use Shaped for multiple ranking use-cases?
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.
How much data do I need?
There is no minimum amount of data required. Collecting interactions, for example clicks, views and or impressions is the only requirement.
Why shouldn’t I build this in-house?
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.
How do you handle my data?
Shaped was built from the ground-up with security as a top priority. We operate as a cloud software-as-a-service (SaaS) platform, and only retrieve from your connected datastores when necessary to build your ranking algorithms. After training, most of your data is discarded, other than specific non-identifiable encoded features that are used at inference. We only require read access to your datasets and customer data never has to be persisted within Shaped.
Shaped
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