Sold by: Quantiful
QU is built on leading edge AI tech, when combined with Machine learning algorithms provides a state-of-the-art AI capability. QU synthesises millions of data points allowing it to predict future buying behavior then uses this insight to adjust forecasts right down to individual product level (sku)
Overview
QU is built on AWS and leverages leading-edge AI technologies which when combined with QU's proprietary Machine learning algorithms affords a highly secure, state-of-the-art AI capability. QU synthesizes millions of data points from hundreds of sources allowing it to predict future buying behaviour then uses this insight to adjust forecasts of future sales right down to individual product level (SKU). QU AI forecasts are illustrated to planning teams for performance and exception management before release to ERP. More accurate forecasts mean stock levels can be lowered with confidence while maintaining or improving availability.QU is built on leading-edge AI technologies which when combined with Machine learning algorithms provides a state-of-the-art AI capability. QU synthesizes millions of data points from hundreds of sources allowing it to predict future buying behaviour then uses this insight to adjust forecasts of future sales right down to individual product level (SKU).
Highlights
- Leading edge AI technologies & ML Algorithms
- Millions of data points from hundreds of sources to create the most accurate forecast of demand
- SaaS Element to illustrate the planning process and performance of the forecast
Details
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Introducing multi-product solutions
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
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Dimension | Description | Cost/month |
|---|---|---|
Quantiful - QU | 1000 SKU's / Products. Forecast Outputs Only. | $5,000.00 |
Vendor refund policy
As a standard practice Quantiful will not refund money. However in extreme cases deemed so by Quantiful a consideration may be made to review a request for a refund.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
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Support
Vendor support
Quantiful Team provides expert general and customized support including documentation, email and phone support. We will respond to any query within 24 hours. support@quantiful.co.nz
AWS infrastructure support
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Machine Learning Algorithms
Proprietary machine learning algorithms combined with leading-edge AI technologies for demand forecasting
Multi-Source Data Integration
Synthesis of millions of data points from hundreds of sources to generate demand predictions
Granular Forecast Capability
Forecast adjustment capability at individual product level (SKU) based on predicted buying behavior
Performance Visualization and Management
SaaS-based interface for illustrating planning process, performance metrics, and exception management of forecasts
ERP Integration
Forecast release capability to enterprise resource planning systems after performance review
Model-Driven Architecture
Uses model-driven architecture to accelerate delivery and reduce complexities of developing enterprise-scale AI applications.
Data Integration and Management
Ingests and manages all relevant data sources from existing internal and external data sources to generate predictive insights.
Entity and Context Extraction
Identifies, extracts, and manages entities and contextual data for enhanced data processing.
AWS Service Integration
Leverages multiple AWS products and capabilities including Amazon EKS, RDS, Bedrock, and SageMaker for building and deploying ML models.
Low-Code AI Application Development
Composable builder for constructing predictive, generative, and agentic workflows without extensive manual coding
Model and Workflow Governance
Built-in capabilities to secure, audit, and monitor models, prompts, and workflows throughout their lifecycle
Multi-Modal Model Training
Support for training across multiple data types and model architectures for both LLM and classical ML workloads
Flexible Deployment Options
Support for SaaS, Dedicated Managed AI Cloud, or self-managed deployment within customer VPC
AI-Ready Data Pipelines
Automated data preparation and pipeline orchestration optimized for reducing time-to-value in AI projects
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