Classical forecasting misses the signals that matter. QuantPi.ai builds AI systems that ingest weather, social trends, competitor data, and market signals to forecast demand, optimize routes, manage inventory, and prevent disruptions — before they happen.
We do not sell generic dashboards. We engineer AI systems tailored to your supply chain.
Connect your ERP, WMS, TMS, IoT sensors, POS systems, and external data sources into a unified analytics platform. We handle the messy data engineering so you do not have to.
Build custom forecasting, optimization, and anomaly detection models trained on your historical data and enriched with external signals. Every model is tuned for your specific supply chain dynamics.
Deploy models into your operational workflows with real-time inference, automated retraining, and human-in-the-loop overrides. Not a research project — a production system.
Models improve automatically as new data flows in. Weekly performance reviews, quarterly model refreshes, and continuous A/B testing ensure your AI gets smarter over time.
ML models that incorporate weather, promotions, social signals, economic indicators, and competitor actions. 25-35% accuracy improvement over statistical baselines. SKU-level, daily granularity.
Real-time routing that factors in traffic, weather, delivery windows, vehicle capacity, and driver constraints. 15-20% reduction in transportation costs.
Dynamic safety stock calculations, reorder point optimization, and multi-echelon inventory planning. Reduce carrying costs while eliminating stockouts.
IoT sensor data + ML models predict equipment failures 2-4 weeks in advance. Schedule maintenance before breakdowns disrupt your operations.
AI monitors global news, weather patterns, geopolitical events, and supplier signals to flag supply chain risks before they impact your operations.
Scenario modeling, what-if analysis, and optimization recommendations. Give your planners AI-powered decision support — not just dashboards, but actionable insights.
High-velocity SKU forecasting, promotional lift modeling, shelf-life optimization, and distribution network planning for fast-moving consumer products.
Raw material demand planning, production scheduling optimization, WIP inventory management, and supplier lead time prediction.
Cold chain monitoring, expiry management, regulatory compliance tracking, and demand sensing for seasonal and pandemic-driven fluctuations.
Omnichannel demand forecasting, last-mile delivery optimization, returns prediction, and dynamic assortment planning.
Just-in-time supply optimization, multi-tier supplier risk monitoring, parts demand forecasting, and aftermarket logistics.
Perishable goods logistics, harvest prediction, cold chain optimization, and farm-to-fork traceability.
ERP systems use statistical methods that miss non-linear patterns. Our ML models incorporate 50+ external signals and learn complex demand patterns that statistical methods cannot capture.
At minimum: 2+ years of historical sales/shipment data. Ideally: SKU-level transactions, supplier lead times, and promotional calendars. We can work with imperfect data — data cleaning is part of our process.
Demand forecasting typically delivers measurable ROI within the first quarter of deployment. Route optimization shows impact within weeks. Most clients achieve full payback within 6 months.
Yes. Pre-built connectors for SAP, Oracle, Microsoft Dynamics, and custom ERPs. We integrate into your existing workflows — no rip-and-replace required.
We train your planning team on the new tools and run parallel operations during the transition. The goal is augmented intelligence — AI enhancing your planners, not replacing them.
That is exactly where AI excels. The more variables, constraints, and data points in your supply chain, the greater the advantage of ML over traditional methods.
Book a discovery call and we will identify the highest-ROI AI opportunity in your supply chain.