ShapedQL
UnclaimedThe real-time retrieval engine for search, feeds, and AI agents, powered by a SQL interface.
Visit WebsiteFreemiumVisit Website
Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Familiar SQL syntax reduces learning curve for developers
Biggest con
Tightly coupled with Shaped platform, not a standalone tool
TL;DR - ShapedQL
- SQL-like query engine for powering search, recommendation feeds, and AI agent retrieval
- Unifies search indexes, recommendation models, and vector stores in a single query language
- Built by Shaped for real-time ranking and personalization at production scale
Pricing: Free plan available
Best for: Growing teams
What is ShapedQL?
ShapedQL is a SQL-like query engine built by Shaped for powering search, recommendation feeds, and AI agent retrieval in real time. It lets developers write familiar SQL-style queries to retrieve and rank results from search indexes, recommendation models, and vector stores through a unified interface. Instead of managing separate APIs for search and recommendations, teams use ShapedQL to combine filtering, ranking, and personalization in a single query language optimized for real-time retrieval.
Available on: Web
Pros & Cons
Pros
- Familiar SQL syntax reduces learning curve for developers
- Unifies search and recommendation retrieval into a single query layer
- Real-time performance optimized for production workloads
- Purpose-built for AI agent and recommendation system use cases
Cons
- Tightly coupled with Shaped platform, not a standalone tool
- New query language with a small community and limited third-party resources
- May be overkill for simple search implementations
Preview
Key Features
SQL-like query language for search, feeds, and AI agent retrievalUnified interface for search indexes, recommendation models, and vector storesReal-time ranking and personalization in queriesCombines filtering, sorting, and ML-based ranking in one languageDesigned for AI agents that need structured retrieval
Pricing Plans
Pricing checked Jun 13, 2026
Free Tier
Free
- Access to ShapedQL query engine
- Basic search and retrieval
- Limited request volume
Enterprise
null
- Unlimited queries
- Custom models and ranking
- Dedicated support
- SLA guarantees
Reviews
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ShapedQL FAQ
How does ShapedQL streamline the development of recommendation systems?
ShapedQL allows developers to combine filtering, ranking, and personalization within a single SQL-style query language. This unifies search and recommendation retrieval, optimizing the process for real-time performance in production workloads.
Which teams benefit most from using ShapedQL?
Teams building AI agents or recommendation systems will find ShapedQL particularly useful. Its real-time retrieval capabilities and unified query layer are purpose-built for these advanced use cases.
What kind of trade-offs should users consider before adopting ShapedQL?
ShapedQL is tightly coupled with the Shaped platform, meaning it is not a standalone tool. Additionally, it introduces a new query language with a smaller community and fewer third-party resources compared to more established options.
How is ShapedQL priced?
ShapedQL includes a free tier for initial use. Paid plans are available, offering expanded usage and additional features for more demanding applications.
Can ShapedQL be used to power AI agent retrieval?
Yes, ShapedQL is purpose-built for AI agent use cases, providing a real-time retrieval engine. It allows agents to query and rank results from various data sources through a unified SQL interface.
How does ShapedQL compare to Hasura for data retrieval?
ShapedQL focuses on unifying real-time retrieval for search, recommendations, and AI agents using a SQL-like interface. In contrast, Hasura primarily provides instant GraphQL APIs over existing databases.
Does ShapedQL simplify querying across different data sources?
Yes, ShapedQL unifies search and recommendation retrieval into a single query layer. It allows developers to write SQL-style queries to retrieve and rank results from search indexes, recommendation models, and vector stores through one interface.
Source: shaped.ai