Contribute to the Standard for Verifiable AI

The promise of generative AI is hampered by a critical flaw: the high cost of trust. For every hour an AI saves in drafting, professionals often spend an equal or greater amount of time manually verifying its output, especially in high-stakes environments. This challenge, the “Verification-Value Paradox,” is what the Verian Standard was created to solve.

Building a truly universal standard requires a community. We are actively seeking contributions from subject matter experts, technologists, and researchers who believe that a verifiable, trustworthy AI is not just possible, but necessary.


Ways You Can Contribute

We welcome different forms of contribution based on your expertise.

1. Share Your Use Case (For Industry Experts)

Are you a lawyer, doctor, financial analyst, or engineer? Your real-world experience is the most valuable asset in shaping this standard. We need to understand your pain points.

  • What high-stakes documents do you review?
  • Where does generative AI fail you today?
  • What would "verifiable proof" look like in your workflow?
Share Your Expertise

2. Develop the Standard (For Technologists)

Are you an engineer, developer, or system architect? Help us build the core protocol. Our specification is developed openly, and we need technical minds to refine, review, and implement it.

  • Review the draft specification.
  • Participate in Technical Working Groups (TWGs).
  • Build proof-of-concept implementations.
View the Spec on GitHub

3. Advance the Research (For Academics)

The "Verification-Value Paradox" is a rich area for research. We aim to collaborate with academic institutions to benchmark, test, and validate the effectiveness of the Verian protocol.

  • Develop testing methodologies.
  • Publish benchmarks and case studies.
  • Explore the theoretical limits of verification.
Collaborate on Research

Our Contribution Process

Our goal is to be open and transparent. Technical contributions are managed through our GitHub repository and future Technical Working Groups. Use case and research contributions begin with a conversation with our formation committee.

We believe that by bringing together the brightest minds from industry and academia, we can build the foundational layer of trust for the next generation of AI.