New study: The Agentic AI gap
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Forecasting software that drives higher accuracy and keeps you ahead of market change
Plug into your ERP, Data Lake, or drop in a CSV and get production-ready forecasts in days, not months. 70+ algorithms, Azure-native, fully self-serve. Prognotix delivers enterprise-grade accuracy without the enterprise cost or complexity.
90 Days
from PoC to Production Value
70+ AI Models
out of the box
<2 Months
ROI
100% Compliant
GDPR, EU AI Act
Still fighting these 3 forecasting problems?
Inaccurate and rigid forecasting in volatile markets
Traditional planning methods struggle to keep up with changing market conditions, leading to poor forecast accuracy, inefficient decisions, and increased risk.
Heavy reliance on IT and data science slows down planning
Forecasting often depends on technical teams, creating bottlenecks that prevent planners from quickly testing assumptions and adapting to new data.
Fragmented systems and data silos limit scalability and trust
Disconnected tools and inconsistent data sources lead to misaligned forecasts, lack of transparency, and difficulty scaling forecasting across the business.
All your forecasting pain, solved with AI built for business users
Maximize forecasting value without disrupting your enterprise landscape
Prognotix is designed to fit into your existing ERP, data, and analytics ecosystem—not replace it. It works alongside platforms like SAP, D365, Oracle, Databricks, Fabric, and Power BI, eliminating overlap and keeping your data unified in a single source of truth.
The result is seamless integration of forecasts into daily operations and strategic decision-making.
Connect your data in minutes and turn it into better forecasts faster
Ingest data directly from Excel or CSV files, connect directly to your Data Lake (Microsoft Fabric or Databricks), or integrate with ERP and other enterprise systems via API. Quickly test assumptions, enrich forecasts with new signals, and iterate without creating effort for IT.
Empower planners without creating IT or data science workload
Prognotix empowers planners to build, test, and refine forecasts independently, without relying on IT or data science. Forecasts are automatically aligned across hierarchies, ensuring consistent, auditable results from SKU to executive level.
With built-in scenario planning, teams can evaluate risks, test assumptions, and make better decisions—transforming forecasting into a fast, agile, and standardized process that adapts to market change.
Reliable forecasts you can explain and audit
From ARIMA and ETS to LSTM, TimeGPT, and further modern deep-learning approaches, prognotix orchestrates over 70 forecasting models and automatically selects the best fit per time series. The agile workflow provides explainability and performance metrics leading to confidence, and trust for operational teams and executive stakeholders alike.
AI forecasting without compromising data sovereignty or compliance
Prognotix runs as an Azure Managed Application within your own tenant, so your data never leaves your environment. This ensures full data sovereignty, enterprise-grade security, and seamless alignment with your existing governance and IT policies.
Scale forecasting across new products, volatile markets, and growing complexity without adding tools or fragmentation- establishing a consistent, transparent standard across your entire supply chain.
Real-world success with AI forecasting
The Zumtobel Group, a global leader in lighting solutions, transformed its complex and manual demand planning processes by adopting an AI-driven forecasting solution. Facing high product variability, volatile demand, and inefficient workflows, the company partnered with paiqo and Microsoft to implement a scalable solution on Azure.
Within months, automated, data-driven forecasts improved accuracy, reduced errors, and increased efficiency across the end-to-end supply chain. This shift enabled better decision-making, more agile planning, and a stronger ability to respond to market changes—demonstrating how AI can unlock measurable value in complex business environments.
SPAR Austria is using AI and data to further reduce food waste across its retail network. In collaboration with SPAR ICS, Microsoft, and paiqo, the company implemented an AI-driven forecasting and ordering solution that analyzes sales, weather, promotions, and seasonality to generate precise, store-level demand forecasts.
With prediction accuracy exceeding 90%, the system ensures the right products are available at the right time, improving efficiency across more than 1,500 stores while reducing waste. Built on Microsoft Azure, the scalable solution supports smarter supply chain decisions—enhancing operations, supporting employees, and delivering measurable environmental impact.
Westfalen Weser Netz (WWN), a German grid operator, is using AI-powered forecasting to manage the growing complexity of modern energy systems. With renewable energy sources like wind and solar introducing high volatility, accurate demand forecasting has become critical to maintaining grid stability and avoiding costly imbalances.
By implementing Prognotix, WWN can automatically evaluate and deploy the best-performing models, incorporating external factors such as weather to significantly improve forecast accuracy. The solution delivers reliable, day-ahead forecasts within tight operational timelines and continuously improves through automated retraining.
Deployed within WWN’s Microsoft Azure environment, the platform ensures full data security while scaling computing resources as needed. Within just two months, the solution matched existing forecast accuracy—with clear potential for further improvements—demonstrating how AI can drive efficiency, reliability, and smarter decision-making in critical infrastructure.
