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Description
Achieve a strategic advantage and sustain a superior position against competitors through an innovative automated system designed to interpret diverse data sources for valuable insights. Our time series forecasting solution, Dominate, meticulously examines economic metrics, global market indices, media trends, and additional data to support effective supply chain management and anticipate potential future scenarios. This state-of-the-art method of data preparation has been validated in some of the most challenging environments worldwide. By employing AI and machine learning, we harness the interconnections between comprehensive data elements to effectively influence your results. Our advanced multi-step, multi-factor, multi-target autoregressive models can accurately predict various values and adjust them as necessary. Dominate offers assurance in shaping circumstances to uncover surprising insights and create groundbreaking strategies. Moreover, our tensor completion technique effectively manages flawed and incomplete data while providing time-series forecasting, alert notifications, and impact assessments. Ultimately, this robust capability empowers organizations to navigate uncertainty and make informed decisions with confidence.
Description
TimesFM-3 represents an advanced time series foundation model that excels in highly precise multivariate forecasting with a single forward pass. This model, which consists of 330 million parameters, has undergone pre-training on a vast corpus of real-world and synthetic time series data, totaling over 1 trillion time points, thereby enhancing the effectiveness and zero-shot generalization capabilities seen in previous TimesFM iterations. It is adept at simultaneously predicting numerous coevolving time series and understanding dependencies that bolster accuracy without the need for task-specific fine-tuning. Furthermore, it accommodates multiple forecasting targets, including both point and quantile predictions, and incorporates past covariates that are only available historically, alongside dynamic covariates that pertain to future events such as planned promotions, holidays, or weather changes. Utilizing a decoder-only transformer architecture, TimesFM-3 processes sequential data in segments of 32 time steps, employing alternating causal temporal attention and full variate attention to integrate patterns across both time and interrelated series effectively. As a result, it provides a robust tool for forecasting complex time-dependent phenomena in various applications.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
BigBear.ai
Country
United States
Website
bigbear.ai/solutions/supply-chain-management/dominate/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/
Product Features
Decision Support
Application Development
Budgeting & Forecasting
Data Analysis
Decision Tree Analysis
Monte Carlo Simulation
Performance Metrics
Rules-Based Workflow
Sensitivity Analysis
Thematic Mapping
Version Control
Supply Chain Management
Demand Planning
Electronic Data Interchange
Import / Export Management
Inventory Management
Order Fulfillment
Order Management
Sales & Operations Planning
Shipping Management
Supplier Management
Transportation Management
Warehouse Management