The startup develops enterprise applications that utilize mathematical modeling, non-linear regressions, and neural networks to optimize supply chain operations. By identifying and eliminating inefficiencies, their software helps clients reduce waste and increase profitability.
Funding
$107M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional supply chain planning systems struggle to handle the increasing complexity and volatility of today's markets, leading to inefficiencies, excess inventory, and suboptimal service levels. Existing Advanced Planning System (APS) software relies on outdated algorithms that fail to account for real-world uncertainties, resulting in unrealistic plans and operational disruptions. Many companies still rely on manual processes and spreadsheets, struggling with departmental silos and slow decision-making.
Solution
Daybreak offers an AI-first supply chain planning platform designed to address the limitations of legacy systems and manual processes. The platform combines an AI Prediction Platform for accurate demand forecasting, an AI-enabled Decision System to facilitate adoption of AI predictions, and an AI assistant, Luma, to automate routine tasks and improve process efficiency. By integrating cutting-edge technology with behavioral science, Daybreak empowers businesses to make faster, more informed decisions, reduce waste, and improve resource utilization. The platform facilitates collaboration between human planners and AI, enabling continuous improvement in decision quality, speed, and confidence.
Target Audience
Daybreak targets supply chain professionals, including demand planners, supply chain executives, and IT users, seeking to improve prediction accuracy, decision quality, and process efficiency in their supply chain operations.
Features
- AI Prediction Platform: A data-centric, domain-specific, and model-agnostic platform for generating accurate supply chain predictions without requiring data scientists or coding skills.
- AI-Enabled Decision System: Combines AI predictions with human judgment to improve decision quality, speed, and confidence.
- AI Assistant (Luma): Automates routine tasks and provides step-by-step guidance through complex supply chain planning trade-offs.
- Data Store: Collects and cleanses raw data from multiple supply chain data sources.
- Feature Store: Processes cleansed data into useful information for AI models, streamlining feature engineering.
- Model Store: Applies a range of proven models to processed data, accelerating model management.
- Decision Quality Score: A metric that reveals patterns in decision-making, identifying areas for improvement.
- Mobile-first design: Enables 24/7 decision power, allowing users to take action from anywhere.