Meet Our Founder
Adrian St. Vaughan MSc CISA MBCS CAMS
CEO & Chief Scientist
Listen to Adrian's Vision
At the heart of LAT is founder Adrian St. Vaughan's personal journey through mental health challenges. Having experienced the limitations of traditional mental health services — which are often accessed only at crisis points when all other coping mechanisms have failed — Adrian recognised a critical gap in mental health support.
"I like to push myself quite close to my limits," Adrian explains. "For me, that's exhilarating, but if you get that wrong, you can sometimes push yourself over the edge. When a crisis point has been reached, you then move onto a medical approach to mental health."
But what if mental health could be maintained proactively through regular practice, just like physical health? We don't wait until we're seriously ill to eat well or exercise regularly, why should we wait until we're in crisis to improve our mental wellbeing?
Adrian brings a rare combination of expertise to the emerging field of AI-assisted mental health support. As a computer scientist working with artificial intelligence since 2017, he approaches this sensitive domain with a unique background:
Risk Management
As Vice President at JPMorgan Chase, Adrian provided board-level assurance for systems handling $3.2 trillion in daily transactions.
Technical Foundation
Adrian's formal training in deep learning allows him to engineer AI systems from scratch rather than relying on off-the-shelf solutions.
Global Perspective
Having directed technology initiatives across the UK, US, Middle East, and Asia, Adrian designs solutions that respect cultural nuances.
Mental Health Focus
Adrian's interest in neurodiversity and mental health has guided his development of speech-to-speech companions for wellness support.
"We can use technology to extend the reach of mental health support, but only if we put privacy, ethics and real human needs at the center of everything we build."
Adrian's Vision for Ethical AI
Privacy by Design
Building systems where personal data stays private and in your control - always.
Human-Centered AI
Designing AI that complements human relationships rather than replacing them.
Ethical Boundaries
Creating AI companions with built-in safeguards and ethical frameworks that prevent potential harms.
Adrian's Approach to AI Innovation
Adrian's unique background in financial security and AI innovation has shaped his approach to building mental health support technology:
- Applying the rigor of financial security to mental health technology
- Building from scratch to ensure privacy and security at every layer
- Ensuring technology supports rather than replaces human connection
- Focusing on preventative support to complement professional care
"The most powerful technologies are those that empower people while respecting their privacy and agency. This is especially true for mental health support, where trust is essential."
Professional Background
Founded LAT
CEO & Chief Scientist
2025 - Present
Launched LAT to make AI-assisted mental health support accessible while prioritizing privacy, ethics, and human connection.
Speech-to-Speech Research & Development
Independent Projects
2016 - Present
Developing speech-to-speech systems with a focus on mental health support and emotional intelligence.
JPMorgan Chase
Vice President, Technology Audit
2012 - 2014
Provided board-level assurance for systems handling $3.2 trillion in daily transactions, developing deep expertise in risk management.
MSc Information Technology
University of Sussex
2003 - 2005
Completed with distinction, developing award-winning research on using eigenvectors to detect word similarities—pioneering work that anticipated modern AI language processing techniques years before they became mainstream.
Certifications & Professional Memberships
From Academic Research to Modern AI
Adrian's Early Contributions to AI
Back in 2005, while completing his degree, Adrian used mathematical structures called "eigenvectors" to detect similarities between words. While this sounds technical, what he was doing was teaching computers to understand relationships between words in a way similar to how our brains connect related concepts.
This approach was truly ahead of its time. Today, we take for granted that search engines understand what we mean, not just what we type. Adrian's award-winning work laid the groundwork for this technology years before it became mainstream.
In Plain English: What Adrian Built
Imagine organizing words in a way that "dog" and "puppy" end up close together, while "cat" is nearby but not as close, and "automobile" is far away. Adrian's system could understand that some words are more related than others, creating a kind of "map" of word meanings. This fundamental approach now powers much of today's AI technology.
Connection to Today's AI Revolution
Then (2005)
Adrian's work used mathematical techniques to capture relationships between words in academic texts, allowing computers to detect similar concepts even when different terminology was used.
Now (Current AI)
Modern AI systems like ChatGPT use more advanced versions of the same fundamental idea to understand language, retrieve information, and generate relevant responses.
The Path from Research to Modern Applications
- Search Engines: When Google shows results that match your intent rather than just your exact words, it's using technology built on principles similar to Adrian's early work
- RAG Systems: Today's Retrieval Augmented Generation systems use vector search to find information that matches a query's meaning - a direct evolution of the eigenvector approach Adrian pioneered
- AI Assistants: When an AI understands what you're asking, it's using embeddings - mathematical representations of meaning that evolved from early research like Adrian's
- Recommendation Systems: Services that suggest products, music, or content based on understanding your preferences use similar mathematical principles
"What's remarkable about Adrian's 2005 work is that he was tackling language understanding with mathematical rigor long before deep learning made these approaches mainstream. The award he received recognized that he was at the forefront of what would become a fundamental technology."
While today's systems use more complex neural networks, the core idea of representing meaning in mathematical spaces where similarity can be measured - exactly what Adrian was doing with eigenvectors - remains at the heart of modern AI. His work was part of the foundation that made today's AI revolution possible.
Connect with Adrian
Adrian regularly speaks on AI ethics, privacy-first technology, and the future of mental health support. He welcomes connections with researchers, mental health professionals, and industry partners.
For speaking engagements, partnerships, or press inquiries, please Get In Touch
Experience LAT For Yourself
Try the technology Adrian has built and see how AI companions can provide meaningful support while respecting your privacy.