Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
LotusEye offers a cloud-based service for AI-driven anomaly detection that autonomously acquires knowledge of standard behavior from numerical or sensor data provided in CSV format and consistently computes anomaly scores to identify irregularities that could signify faults or unforeseen activities, delivering notifications and visual analytics without necessitating any machine learning expertise from users. The service accommodates both wide-format CSV files, where every row corresponds to sensor readings at specific timestamps, and long-format CSV files that include timestamp, sensor name, and value columns, allowing users to upload their data either through a simple drag-and-drop interface or via an API for automated processing on a scheduled basis. Once an AI model is trained using data from normal operations, users can then input test data to obtain calculated anomaly scores and view these results on dashboards featuring time-series graphs, threshold markers, and filtering options, which assist teams in identifying unusual trends and probing potential concerns swiftly. This streamlined process enhances operational efficiency and empowers teams to act on insights generated by the platform.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Google Sheets
No
Microsoft Excel
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$13 per month
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
BigBear.ai
Country
United States
Website
bigbear.ai/solutions/supply-chain-management/dominate/
Vendor Details
Company Name
LotusEye
Country
Japan
Website
lotuseye.co.jp/
Product Features
Decision Support
Application Development
No
Budgeting & Forecasting
No
Data Analysis
No
Decision Tree Analysis
No
Monte Carlo Simulation
No
Performance Metrics
No
Rules-Based Workflow
No
Sensitivity Analysis
No
Thematic Mapping
No
Version Control
No
Supply Chain Management
Demand Planning
No
Electronic Data Interchange
No
Import / Export Management
No
Inventory Management
No
Order Fulfillment
No
Order Management
No
Sales & Operations Planning
No
Shipping Management
No
Supplier Management
No
Transportation Management
No
Warehouse Management
No