Over 50 problem statements solved to Optimize your supply chain

Demand Planning and Forecasting

Accuracy in demand forecasting is critical but hindered by inconsistent data, fragmented sources, and outdated models that miss key market signals.  

The Syren Edge 

  • Integrated data harmonization engine. Minimizes data inconsistencies that hamper planning systems.
  • Advanced machine learning and statistical models for precision forecasting.
  • Feature engineering to capture seasonality, trends, and external factors. 
  • Integrated scenario planning enabled with recommendation engine.
  • Device agnostic  

Smarter, Faster, and More Reliable Forecasting with OptimaDP

Accelerate demand planning, and benefit from adaptive, real-time insights with OptimaDP.

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Struggling with excess inventory in some regions and stockouts in others? This imbalance in traditional inventory models drives up costs and impacts service levels.

The Syren Edge 

  • With dynamic optimization, Syren adjusts inventory levels in real-time based on evolving demand patterns to reduce stockouts in high-demand regions.
  • Our models factor in demand variability and customer service costs to ensure inventory is allocated strategically to meet critical service level commitments without unnecessary stockpiling. 
  • Mixed-Integer Programming (MIP) enables seamless coordination across regions, preventing overstocking in one area while another faces shortage. 
  • Syren’s optimization model integrates real-time data inputs like sales forecasts, allowing for automatic rebalancing of inventory levels across regions. 

Unpredictable lead times disrupt supply chains leading to delays, increased costs, and inefficient logistics operations.

The Syren Edge 

  • Syren uses machine learning models like XGBoost, LSTM, and Bayesian to predict lead times dynamically based on real-time data, supplier performance, weather conditions, as well as geopolitical risks. 
  • Reinforcement Learning (RL) adjusts lead time buffers dynamically, considering variability in demand, production delays, and transportation bottlenecks. 
  • Optimization algorithms like Mixed Integer Programming & Genetic Algorithms balance cost vs. lead time for different products and regions.  

Lead an extensive supply chain network? Inefficiencies in this network cause long lead times, high transportation costs, and underutilized facilities.

The Syren Edge 

  • Syren combines AI-based heuristics with mathematical optimization to speed up decision-making for complex networks while maintaining accuracy. 
  • Multi-objective optimization balances cost, lead time, service levels, carbon emissions, and risk mitigation unlike other approaches with a single objective. 
  • We track demand, logistics, and capacity in real-time. 

Are underfilled containers, poor route planning, and misaligned warehouses driving up costs? Uncoordinated logistics operations lead to inefficiencies, delays, and higher expenses, ultimately impacting service levels and profitability.

The Syren Edge 

  • Syren maximizes space utilization using Mixed Integer Programming unlike static or manual methods. 
  • Dynamic and real-time allocation of products within containers based on demand, order priority, and available space.  
  • Multi-Objective Optimization simultaneously balances cost, order priority, and transportation constraints for the most efficient outcome.
  • Smart Container Selection identifies the most cost-effective container options to minimize shipping costs without compromising service levels. 

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With Syren's help, we identified our high-value customers and kept them coming back

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Optima Control Tower | End-to-End Intelligent Supply Chain 

Real-time, end-to-end, 360° supply chain visibility and AI-driven recommendations to preempt issues, boost efficiency, and strengthen resilience. 

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