Interactive benchmark
Forecasting baseline lab
Explore why naive, seasonal-naive, and moving-average baselines behave differently across transparent synthetic demand patterns.
Run the benchmark →Research + demonstrations
Methods you can inspect, question, and reproduce.
This library separates original technical demonstrations from client case studies. Every asset identifies its data, assumptions, method, limitations, and intended decision use.
Evaluation framework
Knowledge-system evaluation
Define retrieval, answer support, abstention, permissions, latency, cost, and human-review evidence before release.
Use the framework →Future research must disclose the data source and rights, method, sample construction, evaluation design, uncertainty, limitations, authorship, update date, and any code or artifacts needed to understand the result.