Provides a compute engine optimized for running multi-step AI workloads by analyzing and tuning workflows as directed acyclic graphs. Enables developers to build compound AI systems using modular components like models, vector databases, and code interpreters, improving performance through automatic workload optimization and maximum parallelism.
Funding
$7.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Building complex AI systems often requires piecing together various modular components like models, vector databases, and code interpreters. Optimizing these multi-step AI workloads for performance and parallelism can be challenging and time-consuming.
Solution
Substrate provides a compute engine and platform designed to streamline the development and execution of multi-step AI workloads. It allows developers to connect modular AI components into workflows represented as directed acyclic graphs. The platform then automatically analyzes and optimizes these graphs for maximum parallelism and efficiency, reducing roundtrips and improving overall performance. Substrate offers simple abstractions and a unified environment for building compound AI systems.
Target Audience
Substrate targets AI developers and teams building complex AI-powered applications who need a platform to optimize and accelerate their multi-step workloads.
Features
- Compute engine optimized for multi-step AI workloads
- Automatic workload tuning through directed acyclic graph analysis
- Maximum parallelism for efficient execution
- Support for modular components like models, vector databases, and code interpreters
- Simple abstractions for building compound AI systems
- Python and TypeScript SDKs for easy integration