Salesforce's Moirai 2.0 powers zero-shot forecasting in Data 360
Foundation models are moving beyond text into tabular time-series, and Salesforce embedding one directly into its analytics stack signals that zero-shot forecasting is becoming a default enterprise feature rather than a data-science project. Analysts and BI teams on Tableau or Data 360 can trial it without any modelling work, and competitors like Google BigQuery and AWS Forecast now face a ready-built rival. Plans to put Moirai inside root-cause-analysis agents point to where forecasting products are heading next.
Salesforce Research announced that Moirai 2.0, its time-series foundation model, now enables zero-shot forecasting inside Data 360. The model is pretrained on millions of diverse time series to capture seasonality, trends and sudden shifts, letting teams forecast pipeline, service volume, demand and consumption without building custom models. It is integrated into Data 360 Transforms, Tableau Next and D360 SQL, with forecasts starting in minutes rather than weeks of model selection and tuning. Technical details are available in arXiv papers 2402.02592 (Moirai) and 2511.11698 (Moirai 2.0).
Moirai 2.0, our time-series foundation model, now powers zero-shot forecasting in Data 360. Teams can forecast pipeline, service volume, demand, and consumption on trusted enterprise data, with no custom model to build.
Article: https://t.co/5zFklTihDx
From research to product: 🔬 Pretrained on millions of diverse time series to learn seasonality, trends, and sudden shifts ⚡ Forecasts start in minutes, not weeks of model selection and tuning 📊 Built into Data 360 Transforms, Tableau Next, and D360 SQL
Next up: Moirai inside agents that reason over time-series data, explain root causes, and recommend actions.
📄 Papers: arXiv 2402.02592 (Moirai) and 2511.11698 (Moirai 2.0)
✍️ Avni Wadha #TimeSeries #FoundationModels #Forecasting #AIResearch
