AI Infrastructure

Vector Memory Store

A managed vector database tuned for retrieval workloads — fast, filtered, and horizontally scalable.

All products

Filtered nearest-neighbour search

Per-tenant namespace isolation

Scales horizontally as data grows

Overview

The Vector Memory Store is a managed home for embeddings, built for the access patterns retrieval and agent memory actually use: filtered nearest-neighbour search, metadata queries, and namespace isolation per tenant — without you operating a cluster.

How it works

Embed and upsert vectors through a simple API; the store indexes them for filtered nearest-neighbour search across metadata and namespace. Query latency stays flat as your data grows, because the underlying index scales horizontally without you managing shards or clusters.

What's included

A managed vector index, metadata filtering, per-tenant namespace isolation, and horizontal scaling — with no cluster operations on your side.

See it in action

Book a walkthrough and we'll show it running against a stack like yours.

All products

AI Context Platform

A managed context layer that assembles, ranks, and serves the right knowledge to your models on every request.

AI Model Aggregator

One API in front of every major model provider, with routing, fallbacks, and unified billing — an OpenRouter you can run yourself.

Agent Orchestration Runtime

A runtime for multi-step agents — tool calls, state, retries, and human-in-the-loop — running reliably in production.

Prompt Evaluation Suite

Test, score, and regression-check prompts and model changes before they reach production.

Enterprise RAG Gateway

A hardened gateway that adds retrieval, guardrails, and audit logging in front of any model endpoint.