Name
Jan Puncar Brezina
GitHub Handle
@puncar-dev
Tell us about yourself
I am a founder, product leader, and author working at the intersection of open source, decentralized organizations, and AI adoption. Over the past eight years, I have worked across the crypto and open-source ecosystem, including with Gitcoin DAO, helping scale funding efforts that distributed more than $60M to open-source builders. I am the author of How To DAO, published by Penguin Random House, a book on building decentralized organizations inspired by open-source communities. More recently, I worked with ElizaOS to support adoption of its open-source agentic framework. I am now building a new open-source project focused on helping traditional enterprises, including manufacturers, safely and cost-effectively adopt AI across both office and floor operations while keeping reliability and governance under control.
Project Name
Corgtex
Project Repo Link
https://github.com/Corgtexdotcom/corgtex
Stream Date
Dates
09-11-26
Twitter URL
@puncarh2d
LinkedIn URL
linkedin.com/in/puncar
Additional Information
Corgtex is an open-source project focused on helping traditional enterprises adopt AI in a practical, governed, and cost-conscious way. Most AI tools today work well for individual knowledge workers, but many organizations — especially manufacturers and operational companies — need AI that can work safely across office teams, floor operations, internal knowledge, workflows, and existing systems.
The goal of Corgtex is to create an AI operating layer that helps companies map their knowledge, processes, tools, and responsibilities, then use that context to support humans and agents in day-to-day work. This includes AI readiness analysis, company knowledge mapping, workflow support, agent governance, and practical automation for both office and operational environments.
What makes the project important to me is that many traditional businesses want to adopt AI but are concerned about reliability, cost, data privacy, and organizational complexity. Corgtex is designed to help them move from random AI experimentation toward a more structured, transparent, and trustworthy AI-native operating model.
I am building it with open-source principles because I believe the next generation of enterprise AI infrastructure should be inspectable, adaptable, and shaped by the communities and organizations that use it — not only by closed platforms.
Name
Jan Puncar Brezina
GitHub Handle
@puncar-dev
Tell us about yourself
I am a founder, product leader, and author working at the intersection of open source, decentralized organizations, and AI adoption. Over the past eight years, I have worked across the crypto and open-source ecosystem, including with Gitcoin DAO, helping scale funding efforts that distributed more than $60M to open-source builders. I am the author of How To DAO, published by Penguin Random House, a book on building decentralized organizations inspired by open-source communities. More recently, I worked with ElizaOS to support adoption of its open-source agentic framework. I am now building a new open-source project focused on helping traditional enterprises, including manufacturers, safely and cost-effectively adopt AI across both office and floor operations while keeping reliability and governance under control.
Project Name
Corgtex
Project Repo Link
https://github.com/Corgtexdotcom/corgtex
Stream Date
Dates
09-11-26
Twitter URL
@puncarh2d
LinkedIn URL
linkedin.com/in/puncar
Additional Information
Corgtex is an open-source project focused on helping traditional enterprises adopt AI in a practical, governed, and cost-conscious way. Most AI tools today work well for individual knowledge workers, but many organizations — especially manufacturers and operational companies — need AI that can work safely across office teams, floor operations, internal knowledge, workflows, and existing systems.
The goal of Corgtex is to create an AI operating layer that helps companies map their knowledge, processes, tools, and responsibilities, then use that context to support humans and agents in day-to-day work. This includes AI readiness analysis, company knowledge mapping, workflow support, agent governance, and practical automation for both office and operational environments.
What makes the project important to me is that many traditional businesses want to adopt AI but are concerned about reliability, cost, data privacy, and organizational complexity. Corgtex is designed to help them move from random AI experimentation toward a more structured, transparent, and trustworthy AI-native operating model.
I am building it with open-source principles because I believe the next generation of enterprise AI infrastructure should be inspectable, adaptable, and shaped by the communities and organizations that use it — not only by closed platforms.