Frontier
Retrieval Stack.
Retrieval engine, models, and inference built together.
Flexible primitives for AI teams pushing the frontier of accuracy, performance, and scale.
BUILT FOR ACCURACY
Find the right context.
Give your applications the retrieval quality they deserve. Multi-vector models and a purpose-built engine, optimized together.
Accuracy across real-world domains
Recall · higher is betterENGINEERED FOR SCALE
Unlimited scale with predictable latency.
Scale to billions of documents per partition with predictable latency and cost. Built on object storage, ready for your most ambitious workloads.
SECURE BY DESIGN
Your data
stays yours.
Enterprise security, built into every layer. Encrypted data, scoped access, and continuously audited infrastructure. Deploy in your VPC or on-prem when you need full control.
Encrypted, everywhere.
Data is encrypted at rest and in transit.
Fine-grained access.
Role-based permissions for your team.
Every action, accounted for.
Audit logging for visibility and control.
On your infrastructure.
Private deployment in your VPC.
PUSHING THE RETRIEVAL FRONTIER
Latest posts
Deep dives into search, retrieval, and what we’re building.
Explore the blog
The Fastest Regex Is the One You Don’t Run
Why AI agents reach for regex search, and how TopK uses sparse n-grams to make those queries fast.
RAG Is Broken for Agents. Here's How We Fixed It.
Context is a search problem. Without the right context, even the best models fail. This post describes why dense embedding based RAG is broken for agents and how multi-vector (late interaction) retrieval fixes it.
TopK SQL: A Search Query Language
TopK now implements the Postgres wire protocol, so any Postgres client can run semantic search, hybrid search, and filtered retrieval as ordinary SQL.
Ship better
search today.
Build on flexible primitives and focus on
what makes your beer taste better.