DAGWorks

About DAGWorks

DAGWorks provides an open-core platform that enables data science teams to efficiently develop and maintain machine learning pipelines using Hamilton for rapid iteration and Burr for building and debugging RAG and agentic applications. The platform enhances observability and state management, allowing teams to deliver reliable AI solutions faster while ensuring data provenance and lineage.

```xml <problem> Data science teams face challenges in efficiently developing, debugging, and maintaining complex machine learning pipelines, especially for Retrieval-Augmented Generation (RAG) and agentic applications. Lack of proper observability, state management, and data provenance tracking hinders the delivery of reliable AI solutions. </problem> <solution> DAGWorks offers a platform centered around Hamilton and Burr, designed to streamline the development and maintenance of machine learning pipelines. Hamilton accelerates the iteration process for Python-based pipelines, while Burr facilitates the building and debugging of RAG and agentic applications. The platform provides enhanced observability features, including data provenance and lineage tracking, and robust state management capabilities. By integrating with existing observability tools, DAGWorks enables data science teams to deliver AI solutions more rapidly and with greater reliability. </solution> <features> - Hamilton: A framework for building Python pipelines with a focus on rapid iteration. - Burr: A framework for building and debugging RAG and agentic applications. - Hosted Hamilton UI: A SaaS offering that provides provenance, lineage, observability, and cataloging for Hamilton pipelines. - Burr Cloud: A hosted execution environment for Burr, offering state management, persistence, and observability. - Integration with existing observability tools. - Data provenance and lineage tracking. - State management and persistence for RAG and agentic applications. </features> <target_audience> The primary target audience consists of data science teams and machine learning engineers involved in developing and deploying AI-powered applications, particularly those working with RAG and agentic systems. </target_audience> ```

What does DAGWorks do?

DAGWorks provides an open-core platform that enables data science teams to efficiently develop and maintain machine learning pipelines using Hamilton for rapid iteration and Burr for building and debugging RAG and agentic applications. The platform enhances observability and state management, allowing teams to deliver reliable AI solutions faster while ensuring data provenance and lineage.

Where is DAGWorks located?

DAGWorks is based in San Francisco, United States.

When was DAGWorks founded?

DAGWorks was founded in 2022.

How much funding has DAGWorks raised?

DAGWorks has raised 500000.

Who founded DAGWorks?

DAGWorks was founded by Elijah ben Izzy.

  • Elijah ben Izzy - Co-founder/Co-creator of Hamilton/Burr OS libraries
Location
San Francisco, United States
Founded
2022
Funding
500000
Employees
3 employees
Major Investors
Y Combinator, Other People's Capital (OPC)
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DAGWorks

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

Executive Summary

DAGWorks provides an open-core platform that enables data science teams to efficiently develop and maintain machine learning pipelines using Hamilton for rapid iteration and Burr for building and debugging RAG and agentic applications. The platform enhances observability and state management, allowing teams to deliver reliable AI solutions faster while ensuring data provenance and lineage.

dagworks.io300+
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Crunchbase
Founded 2022 – San Francisco, United States

Funding

$

Estimated Funding

$500K+

Major Investors

Y Combinator, Other People's Capital (OPC)

Team (<5)

Elijah ben Izzy

Co-founder/Co-creator of Hamilton/Burr OS libraries

Company Description

Problem

Data science teams face challenges in efficiently developing, debugging, and maintaining complex machine learning pipelines, especially for Retrieval-Augmented Generation (RAG) and agentic applications. Lack of proper observability, state management, and data provenance tracking hinders the delivery of reliable AI solutions.

Solution

DAGWorks offers a platform centered around Hamilton and Burr, designed to streamline the development and maintenance of machine learning pipelines. Hamilton accelerates the iteration process for Python-based pipelines, while Burr facilitates the building and debugging of RAG and agentic applications. The platform provides enhanced observability features, including data provenance and lineage tracking, and robust state management capabilities. By integrating with existing observability tools, DAGWorks enables data science teams to deliver AI solutions more rapidly and with greater reliability.

Features

Hamilton: A framework for building Python pipelines with a focus on rapid iteration.

Burr: A framework for building and debugging RAG and agentic applications.

Hosted Hamilton UI: A SaaS offering that provides provenance, lineage, observability, and cataloging for Hamilton pipelines.

Burr Cloud: A hosted execution environment for Burr, offering state management, persistence, and observability.

Integration with existing observability tools.

Data provenance and lineage tracking.

State management and persistence for RAG and agentic applications.

Target Audience

The primary target audience consists of data science teams and machine learning engineers involved in developing and deploying AI-powered applications, particularly those working with RAG and agentic systems.