# MoiraiAgent

Salesforce AI Research has open-sourced GIFT-Eval-CTX, a benchmark for whether forecasting systems can turn forward-looking business context into accurate numerical predictions. Traditional time-series foundation models take numerical history and predefined variables, so they struggle to use known future events such as heatwaves, road closures or software releases. The benchmark splits context into macro trends and micro events across 10,000 tasks from 20 real-world datasets; adding structured future context cut GPT-5.6 Sol's error by 40.7% and Claude Opus 4.8's by 29.6%.

Salesforce AI Research has open-sourced GIFT-Eval-CTX, a benchmark for whether forecasting systems can turn forward-looking business context into accurate numerical predictions. Traditional time-series foundation models take numerical history and predefined variables, so they struggle to use known future events such as heatwaves, road closures or software releases. The benchmark splits context into macro trends and micro events across 10,000 tasks from 20 real-world datasets; adding structured future context cut GPT-5.6 Sol's error by 40.7% and Claude Opus 4.8's by 29.6%.