Making time-series data useful to agents.
The questions, methods, and evidence behind our work.
Start here · 5 min read
A useful answer connects a precise question to the right readings, their meaning, and the sources that let someone check the conclusion. A public building-energy example makes that contract concrete.
Read the articleMethods6 min read
One operational dataset can support a lookup, a comparison, an investigation, or a forecast. The question determines the method—and the evidence needed to trust its result.
Evaluation5 min read
An operational explanation must survive checks on the readings, the conclusion and the proposed action. Here is how to evaluate those separately, including when an agent should say it does not know.
Measurement5 min read
A smaller tool response is easy to measure. A cheaper, equally useful investigation takes a more careful comparison. Here is the calculation, from a saved file to an annual estimate.
Engineering5 min read
A fair pilot compares direct tools, the platform you already use and an agent with Reific on the same work. Define the comparison before spending engineering time on integration.
Published research
A closer look at rare-event forecasting: what a probability means, how an alert changes a decision, and what the evidence supports.
Read the paper explainerICLR 2026 · Main conference
EVEREST: A Transformer for Probabilistic Rare-Event Anomaly Detection with Evidential and Tail-Aware UncertaintyTSALM · ICLR 2026 workshop
Forecasting Solar Flares with the EVEREST TransformerPublic data, exact computations, and downloadable evidence.
Building energyReference replay
A week of building measurements becomes one inspectable energy event, with the original readings and the limits of the conclusion attached.
Room sensorsReference replay
A sharp CO₂ increase looks consequential. The separately recorded occupancy labels tell a different story—and show why an evidence packet must preserve uncertainty.