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About Vector Vault

Vector Vault is a hosted runtime for AI agents with persistent memory. The platform combines a visual builder, Vector Flow, with the Persistent Agentic Runtime (PAR) to make stateful, long-lived agents practical for production workloads.

What Vector Vault Provides

The platform is designed for teams that need reliable, agentic systems without maintaining their own orchestration layer or infrastructure.

  • A persistent runtime for agents that can pause, resume, and branch safely
  • Visual workflows that map directly to a durable execution graph
  • APIs and SDKs for integrating agents into existing products and systems
  • Built-in observability, logging, and performance characteristics suitable for production use

Origins

Vector Vault originated from work on large-scale retrieval-augmented generation systems, where maintaining conversational context and operational state over time proved unnecessarily complex.

Rather than extending ad-hoc infrastructure for each new agent, the team formalized a general runtime—separating stateless compute from durable state—and built Vector Flow as the visual layer on top of that foundation.

Mission

The mission of Vector Vault is to make agentic systems operationally straightforward: predictable to run, simple to integrate, and robust enough for critical workloads.

  • Reduce the infrastructure burden of building and operating AI agents
  • Provide a clear execution model for long-running, stateful workflows
  • Offer tooling that supports both experimentation and production at the same time

Who Uses Vector Vault

Vector Vault is used by product teams, platform groups, and automation leaders who need agents to behave consistently across customer-facing and internal workflows.

  • Organizations building multi-step support, operations, or intake agents
  • Teams standardizing on a single runtime for multiple AI initiatives
  • Companies that require observability, SLAs, and predictable performance from AI systems

Get Started

Teams typically start by designing a single agent in Vector Flow, integrating it via API, and then expanding to additional workflows as requirements grow.

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