Independent · New York
TenTwo Labs takes dense, unstructured material — coursework, scientific literature, experimental data — and gives it a structure you can actually work with.
Most tools hand back prose about your material. We return the artifacts you work against — outlines, question sets, flashcards, mind maps — because understanding is built on structure, not on more paragraphs to read.
Correctness alone is a weak signal. We capture confidence alongside it, so the system can separate knowing something from guessing it — and so a learner sees precisely where they are wrong about being right.
Review timing is computed per item by a spaced-repetition scheduler (FSRS), not set by a fixed calendar. Different material decays at different rates for different people; the schedule should follow the evidence rather than the syllabus.
One person’s material is the easy case. The same operation at the scale of a whole field is the interesting one.
Many sources, claims that disagree, and evidence that accumulates until it occasionally overturns what came before.
That is where the work is heading: knowledge held as a structure with lineage rather than a pile of documents, so a claim’s origin, the evidence beneath it, the confidence it warrants, and the way it has shifted over time are all first-class. Nothing to announce yet.
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