Working demonstrations, not screenshots.

Watch a legal question move through hybrid retrieval, reranking, and citation grounding.

ProvesWhy hybrid retrieval plus reranking beats either keyword or vector search alone — and why an answer should carry its citations.

Four ways to score the same flight — matrix, weighted, probabilistic, and tail-risk.

ProvesTwo flights with the same average risk can have very different worst cases. Decision tools should surface the tail.

Edit a contract clause and watch an auditable rules engine decide: approve, flag, or escalate.

ProvesHigh-stakes legal automation earns trust by being auditable — every decision traces to the rule, fact, and evidence that produced it.

Two models, the same accuracy — one you can trust in a high-stakes loop, one that will hurt you.

ProvesAccuracy hides whether a model knows when it's right. In a system allowed to abstain, calibration — not accuracy — decides whether the confidence threshold means anything.

Ship a detector and start a clock — the other side begins routing around it the same day.

ProvesA static detector always loses eventually. Opacity buys time and retraining resets the clock, but neither wins the arms race — and the threshold can't chase forever without flagging legitimate traffic.

The shape of process that built this site — agents that research, build, and adversarially verify in parallel.

ProvesBounded parallel agents collapse wall-clock time when their work is genuinely independent, and an adversarial verifier that is not the author catches defects a single confident pass ships right past.

Put a wine and a palate on the same eight axes and predict who will actually enjoy the bottle — with the reasons and the uncertainty shown.

ProvesPersonal enjoyment isn't a universal score — it's a match between two profiles on shared axes, and an honest version shows which dimensions drive it and how sure it is.