TopK
TopK combines retrieval, models, inference, and storage for AI teams building search and retrieval systems.
About TopK
TopK is a retrieval stack for AI teams that combines a retrieval engine, models, inference, and storage in one system. It is listed under APIs and databases and is accessed through the web with documentation and API-based building blocks.
With TopK, developers can build enterprise search, visual document retrieval, and agentic search. The system supports dense, sparse, multi-vector, and regex search with filters. It also handles partitioned multi-tenant collections and reports figures such as 1B+ documents per partition and data freshness under 1 second. Security features include encryption at rest and in transit, role-based permissions, audit logging, and private deployment in a VPC or on-prem.
TopK suits developers and AI teams building search and retrieval systems that need to combine models, inference, and storage. It is described for teams working with enterprise search, visual documents, and agent-based applications.
Key features
- Unified retrieval engine with inference and storage
- Supports dense, sparse, multi-vector and regex search
- Filtered search with partitioned multi-tenant collections
- Visual document retrieval for tables and figures
- Private deployment in VPC or on-premises
- Encrypted data with role-based access and audit logging
Best for: AI teams and developers building search, retrieval, or agent-based applications.
Good for
- Combines engine, models, inference and storage
- Supports dense, sparse, multi-vector and regex methods
- Lists VPC deployment with encryption and audit logging
- Publishes scale, latency and freshness figures
TopK at a glance
- Website
- topk.io
- Category
- Development › APIs & Databases
- Type
- Website
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
Guides for APIs & Databases
TopK alternatives
Tools and sites you could use instead, ranked by how closely they match.
Build applications on Gel, an open-source database with a data model, graph queries, authentication, and AI features.
Build APIs with FastAPI, a Python framework described as easy to learn and ready for production.
Vector similarity search is provided by Qdrant, an open-source search engine written in Rust.
Distributed vector search is provided by Vald, an engine designed to scale across deployments.
Open source
24 alternatives
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TopK FAQ
What is TopK used for?
TopK provides a retrieval engine, models, inference and storage for building enterprise search, visual document retrieval and agentic search.
What types of search does TopK support?
It lists support for multi-vector, dense, sparse and regex search, along with filters.
Does TopK support private deployment?
Yes. It lists private deployment in a VPC or on-prem, with encryption, role-based permissions and audit logging.
What scale does TopK report?
It states 1B+ documents per partition, under 100ms p99 latency at 1B documents, and under 1 second data freshness.
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