AI & machine learning research
Hatteria Labs studies how language models work from the inside. We publish what we find — including the results that failed — and build products on the parts that hold up.
Empirical work on model internals: memory compression, weight structure, quantisation, hybrid architectures. Every claim carries a null control it has to beat.
Methods, thresholds and negative results, in the open. A rejected hypothesis is a finding — it is where most of the value in this work lies.
Three products in production, built and run by the same people who do the research. What we learn goes into software people pay for.
Products
Each product is live, paid for by its own users, and runs on our own servers in the European Union. They fund the research and keep it anchored in what works outside a benchmark.
torumata.com
An audit for the era of AI search — see how language models actually read your site.
For: Site owners and marketing teams whose traffic is moving from search results to chatbot answers.
aidj.cloud
The DJ that runs your party on autopilot.
For: Weddings, company parties, bars and clubs, birthdays and school events — anywhere the music matters and nobody should have to spend the evening managing a playlist.
slidify.cloud
Your guests' photos, live on the screen.
For: Anyone hosting a wedding, a celebration or a company event who would rather collect the evening's photographs as they are taken than retrieve them afterwards.
How we work
Most of what looks like a result in machine learning is a measurement artefact. Our process is built around catching our own.
Alongside our own products we accept a limited number of research and engineering engagements — typically where a question needs to be measured properly before anyone builds on the answer.
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