Flowlity vs replenishment

Flowlity is an AI-powered supply chain forecasting and planning solution for manufacturers, distributors, and retailers. Its platform covers demand planning, inventory optimization, supply planning, sales and operations planning, and collaborative planning. Probabilistic forecasts are generated at SKU level from a company’s sales history and supply chain data, helping planners account for uncertainty in demand or lead times. Recommendations can factor in minimum order quantities, batch sizes, full truck or container loads, and Incoterms. The AI monitors spikes, anomalies, and stockouts, and corrects outliers with synthetic resampling. Flowlity lists connectors for SAP, Oracle, Microsoft Dynamics, Cegid, Odoo, and Sage, plus API and SFTP data transfers. Flowlity Lite costs €249 a month, supports up to 5,000 SKUs, and relies on CSV uploads rather than native ERP integration. Enterprise pricing depends on SKU count or inventory value and includes a one-time implementation fee. The company says customer data is hosted in Azure data centers in France, isolated by customer, and encrypted in transit and at rest.

replenishment is a Python library for simulating stock replenishment, optimizing policies, and visualizing policy behavior. It is designed for teams comparing policies against historical or synthetic demand. Listed optimization workflows include safety stock based on mean forecasts, k*RMSE or k*MAE, and percentile targets. For k*RMSE and k*MAE, safety stock can optionally increase when lead-time forecast quantities rise above a baseline. The library supports moving between CSV or DataFrame inputs and simulation configurations, and it can show visual comparisons of policies on replenishment time series. The README includes notebooks for policy variants, synthetic data generation, and loading stock replenishment data. Installation is through PyPI with `pip install replenishment`. The project is tested on Python 3.10, 3.11, 3.12, and 3.13; listed dependencies include pandas, Polars, PyArrow, matplotlib, ipykernel, and scienceplots. The package uses the MIT license and is classified as Alpha. The project welcomes contributions. Minimum order quantities, case-pack constraints, and promotion-aware demand handling are listed as areas for future contribution.