Strake FAQs

Question 1

What is Strake and its core purpose?

Accepted Answer

Strake is the AI Data Layer, providing AI agents with governed, zero-copy access to your entire data stack through a high-performance federated SQL engine. It enables agents to securely discover, query, and process data without movement.

Question 2

How does Strake ensure data security for AI agents?

Accepted Answer

Strake enforces strict read-only access by default, dynamic Row-Level Security (RLS), and PII masking. Agent execution occurs in secure native OS sandboxes or ephemeral MicroVMs for hardware-level isolation.

Question 3

What is 'Zero-Copy Federation' and its benefit?

Accepted Answer

Zero-Copy Federation allows AI agents to query diverse data sources (Postgres, S3, REST, gRPC) simultaneously without data movement or ETL. This reduces latency, cost, and complexity by leveraging Apache Arrow with Pushdown optimization.

Question 4

Can AI agents execute custom logic within Strake?

Accepted Answer

Yes, Strake's 'Code Mode' enables agents to run Python scripts inside secure OS sandboxes or MicroVMs. This allows them to process data where it lives, preventing context bloat by sending only parsed, relevant results to LLMs.

Question 5

What types of data sources can Strake connect to?

Accepted Answer

Strake provides zero-copy integration with a wide range of sources, including PostgreSQL, S3, local files, REST APIs, and gRPC. It supports federated queries across these diverse sources simultaneously.

Strake

Strake

Key Features

Use Cases

Key Features

Use Cases