Substrate

About Substrate

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.

```xml <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. </problem> <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. </solution> <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 </features> <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. </target_audience> ```

What does Substrate do?

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.

Where is Substrate located?

Substrate is based in East New York, United States.

When was Substrate founded?

Substrate was founded in 2023.

How much funding has Substrate raised?

Substrate has raised 7840000.

Who founded Substrate?

Substrate was founded by Ben Guo, Rob Cheung and Kyle Pitzen.

  • Ben Guo - cofounder
  • Rob Cheung - Co-Founder
  • Kyle Pitzen - Co-Founder
Location
East New York, United States
Founded
2023
Funding
7840000
Employees
7 employees
Major Investors
Lightspeed Venture Partners
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Substrate

Score: 100/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

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.

substrate.run700+
cb
Crunchbase
Founded 2023East New York, United States

Funding

$

Estimated Funding

$7.8M+

Major Investors

Lightspeed Venture Partners

Team (5+)

Ben Guo

cofounder

Rob Cheung

Co-Founder

Kyle Pitzen

Co-Founder

Company Description

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.

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

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.