DeepVu provides Generative AI decisioning agents that utilize reinforcement learning and multi-scenario digital twins to enhance supply chain resilience, sustainability, and profitability. The platform enables real-time, data-driven planning decisions that optimize key performance indicators while addressing risks and inefficiencies in supply chain operations.
Funding
$500K 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 relies on forecasting models that struggle to adapt to unexpected disruptions and external shocks, leading to inefficiencies, increased costs, and a lack of resilience. Existing approaches often fail to incorporate a wide range of relevant external signals and lack the real-time adaptability needed to navigate dynamic market conditions.
Solution
DeepVu offers a Generative AI-powered platform that enhances supply chain resilience, sustainability, and profitability through optimized, high-frequency planning and operational decisions. The platform utilizes reinforcement learning and multi-scenario digital twins to empower human planners with AI decisioning agents that can navigate risks and optimize key performance indicators. By leveraging rich, industry-specific supply chain knowledge graphs and real-time data streams, DeepVu enables proactive mitigation of potential disruptions and continuous improvement across various supply chain functions. The system integrates seamlessly with existing ERP systems via cloud APIs or can be used via a dashboard to boost planner productivity.
Target Audience
DeepVu targets manufacturers and businesses seeking to improve the resilience, efficiency, and sustainability of their supply chain operations, particularly those in industries prone to disruptions and external shocks.
Features
- Generative AI decisioning agents trained with reinforcement learning and human feedback
- Multi-scenario digital twins that simulate normal and shock scenarios to recommend optimized actions
- Rich industry-specific supply chain knowledge graphs incorporating hundreds of external signals
- Real-time data analysis of external signals to enrich decisioning agents with current global context
- Integration with existing ERP systems via cloud APIs or a user-friendly dashboard
- AI agents for order fulfillment, demand planning, procurement, production planning, and logistics
- Sustainability KPI tracking to optimize for reduced emissions and resource consumption