Shaped
AI-native platform for real-time recommendations and semantic search.
What is Shaped?
Shaped (also known as Shaped AI) is an AI-native personalization platform built for technical teams to rapidly experiment with, build, and deploy real-time semantic search APIs and training ranking models in recommendation systems. Unlike traditional keyword systems or simple collaborative filtering, Shaped relies on a sophisticated two tower recommendation system architecture. This two tower approach utilizes a multi modal encoder to transform unstructured text, images, and user interactions into deep embeddings, allowing it to efficiently handle cold-start scenarios. Operating as a unified, state-of-the-art model library, it enables real-time learning loops from behavioral signals, fine-tuning transformers and neural ranking models to maximize metrics like precision@k and recall@k for platforms optimizing complex business objectives.
Category
Best Shaped use cases by task, role, industry, and platform
These use cases show where Shaped fits best, ranked by fit score before popularity or pricing.
Shaped Pricing Plans
Compare Shaped free options, Shaped paid pricing plans, and usage notes before you choose the best way to use this AI tool in 2026.
Contact for Pricing
Pricing updated:Jun 12, 2026
Shaped AI Features
Shaped Pros and Cons
Pros
- Built natively for ML workflows, giving engineers full visibility and control over model internals
- Real-time re-ranking loop updates within session contexts
- Combines search and recommendations into a single cross-learning platform unlike Algolia
- Handles unstructured data and cold starts exceptionally well using multi-modal embeddings
- Guaranteed metric lift within the first 30 days or money back
Limitations
- Requires engineering or developer expertise to implement via SDKs or APIs
- Pricing is not transparently listed and requires booking a demo