About Me

image

Hello! Thanks for dropping by to my little corner of the internet :)

I’m Tony, the Applied AI Lead at Verodat, where I am building more robust and trustworthy AI  applications on top of our unique data supply chain platform.  I am also involved in research with the Yale/EPFL LiGHT lab, where I work with the Red Cross, using modular neural networks for humanitarian datasets with systematic missingness.

Our Mission

I work at a mission-driven company.

We believe that data is key to successful AI business implementation.

The current state of business data consistently falls short of what AI needs to deliver its full potential. This gap is where our data supply chain comes into play. We aim to create a consistent, reliable interface for accessing and utilising data, ensuring it is enriched with context, history, provenance, and attribution. This approach transforms data into a powerful asset that AI can leverage with confidence and trustworthiness.

The Thesis

Our thesis is simple yet profound: The right data unlocks AI's potential. By providing AI with well-structured, contextualised data, we can enable organisations to deploy AI solutions that are not only effective but also transparent and verifiable. This leads to better decision-making, optimised operations, and greater success. We want to democratise AI by making it easier for organisations without deep AI expertise to realise its benefits.

Building a Community

We recognise that solving the AI data problem is a collaborative effort. We are building a community of like-minded individuals and organisations who share our commitment to advancing AI through better data. This community is a space for sharing ideas, discussing challenges, and developing solutions together. We believe in the power of collective intelligence and are eager to engage with others passionate about this mission. We don’t think we have all of the answers and want people to join us on a journey where we can solve the AI data problem together.

The Journey So Far

Our data supply chain platform has existed for several years and has been used for various use cases, but we are improving it with the specific aim of providing AIs with the right data. We are creating new APIs, connectors to data sources and are generally working to improve our user experience.

To show how having the right data can unlock AI’s potential, we have built the AI ESG Report Builder. The Report Builder consists of a web app which connects to your data pipeline, pulling in data with context and attribution by using the relevant APIs, presents the relevant data to an LLM agent, which uses it to create tailored ESG reports with narrative.  We’ve open-sourced the solution; it’s available for use here, and you can check out the code and documentation on GitHub.

This tool demonstrates how our data-supply chain can revolutionise ESG reporting by automating the generation of comprehensive, accurate, and tailored reports. Furthermore, it proves generally how our platform can be used to ensure that AIs can be safely used in a business context without the risk of making up key facts and figures.

Join Us

We invite you to join us on this exciting journey. Whether you are an AI enthusiast, a data expert, or a business leader looking to harness the power of AI, there is a place for you in our community. Together, we can solve the AI data problem and unlock new possibilities for businesses worldwide.

You can join the community on Slack here, find me on LinkedIn here and on Twitter here.

Blog Posts and Papers

Data Supply Chain for AI Framework V1.1
Blog Post
June 12, 2024
Doing Data Better: Learnings from the ESG Use Case
Blog Post
June 10, 2024
Note from the CEO
Blog Post
May 30, 2024
Implementing Logistic Regression from Scratch
Deep Learning 101Blog Post
A deep learning approach for maize lethal necrosis and maize streak virus disease detection
PaperComputer Vision