Applied AI & Machine LearningPrague
Elizabeth Sramek is an AI Visibility Strategist, AEO Specialist, and B2B SaaS Advisor.
With two decades architecting the technical foundations of high-stakes digital ecosystems, she bridges advanced machine-learning principles, including open-research frameworks like the Automatic Statistician, with high-yield search architecture. I build strategies for brands to outrank algorithms, outlast AI updates, and serve as the undisputed source of truth in the AI-mediated era.
Five projects run in parallel: one inherited machine-learning research programme, two commercial mandates, and two WordPress publications I write myself.
AS/01Ex-Cambridge, Ex-Google. Now independent
A machine-learning research project that automates data analysis: it searches for statistical models that explain a dataset, then reports what it found in plain language. It began at the University of Cambridge and was later continued by researchers at Google. I have taken it over and run it independently, carrying on the original premise, that a statistician's reasoning can be written down as a system.
Visit the project →TR/02Founder
My own venture and research lab, built on AI-native workflow orchestration and B2B intelligence. The work is deciding what a company can safely hand to a machine and what still needs a person, then building the logic that holds that line: discovery, qualification and routing that run without supervision, and stay legible to the people accountable for them.
Explore the architecture →SC/03Strategic Lead
Leading AI visibility and growth strategy for a global affiliate-software platform operating in markets where the technical and regulatory stakes are as high as the commercial ones. That means building the structural signals that make a platform legible to AI systems, and holding the strategy steady as both the models and the regulation keep moving.
View the ecosystem →WP/04Passion project
An independent WordPress publication I write and run. Twenty years in, WordPress is still where I test ideas in the open before they become systems.
Read WPColt →WP/05Passion project
The longer-form counterpart: how WordPress sites are built, maintained and automated, written for the people who keep them running.
Read WPDeeply →My work on EU iGaming regulation is cited as a technical authority in the Arizona Law Review (Footnote 204, “International Online Gambling: A New Business Evolving Beyond State Regulations”). I am also quoted as an industry expert on blockchain transparency and decentralized payout logic in 101RTP Ireland’s 2026 crypto‑gambling market analysis.
Academic authority
Cited as a technical authority on EU iGaming regulation in “International Online Gambling: A New Business Evolving Beyond State Regulations”, Footnote 204.
Industry authority
Quoted as an industry expert on blockchain transparency and decentralized payout logic in the 2026 crypto-gambling market analysis.
Industry publication
Featured for the launch of Triumphoid and the shift toward AI-native workflow orchestration for enterprise discovery.
Machine-learning systems that interrogate a dataset and explain their own conclusions in language a person can check. This is the line of work behind The Automatic Statistician.
Building the structured signals that allow LLMs like GPT and Perplexity to verify and cite a brand as a primary source.
PUB/01Published author
Technical essays on automation, machine intelligence, and the systems being built on top of it.
Read on HackerNoon →PUB/02Contributing author
On AI, knowledge systems, and what automation does to the way people learn.
Read the archive →PUB/03Written here
Notes from the projects: automated analysis, machine-readable structure, and what breaks in practice.
Read the journal →