Building a universal predictor for applied ML, data science, and annotation.
We are an AI lab for applied ML and data science. We reverse engineer, interpret, and build universal predictors that research groups and machine learning teams can tune to their data. Our mission is applied prediction that compounds over time for all, enabling labs to understand what models learn and teams to run classification, annotation, and decision work across tables and media, growing one base with every new workload towards better and safer intelligence across physics, life sciences, industrial, frontier and critical verticals.
Backed by
awesome programs.
Introducing Aleph
We're heading towards a future where applied ML sits in every vertical that needs a right answer: tables, media, annotation, and decisions, and it's critical the model keeps learning as the work arrives. We're building Aleph, a universal predictor for applied ML and data science. One base. Any modality. Any task. Fine-tune into anything and keep getting better. Not a chat assistant. Schema-bound outputs for programs: probs, labels, boxes, scores, with confidence so you escalate the unsure. Built from scratch for precision and intent, deliberately, not by guessing.
Training SAEs on a LLM to sense conflict, ambiguity, and tone, and choose the right response.
Labs we've worked with
Our latest research
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