Manhattan Active Inventory Replenishment vs supplychainpy
Manhattan Active Inventory Replenishment
manh.comsupplychainpy
supplychainpy.orgSide by side
| Figure | Manhattan Active Inventory Replenishment | supplychainpy |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 0 | 1 |
| Spec score · Inventory Optimization Software | 7.4 (#13) | 7.9 (#3) |
| Founded | 1990 | 2016 |
| Integrations | The ActivePlatform exposes REST APIs and supports synchronous HTTP and asynchronous messaging integrations with enterprise systems, supply chain partners, and automation equipment. | The maker describes use with Pandas, Jupyter, Matplotlib, openpyxl and xlwings. |
| Intended users | Manhattan describes replenishment use cases for wholesale, health and life sciences, and retail organizations. | The maker describes it as a decision support tool for analysts in commercial inventory and demand planning roles. |
| Purpose | ActivePlanning uses AI-powered replenishment to optimize stock across supply chain echelons and nodes. | Supplychainpy is a Python library for supply chain analysis, modeling, and simulation. |
Plans
Manhattan Active Inventory Replenishment
No plans published.
In their own words
Manhattan Active Inventory Replenishment
Manhattan Active Inventory Replenishment has no write-up on Specifiction yet; its figures are above.
supplychainpy
supplychainpy is a Python library for supply chain analysis, modeling, and simulation, aimed at commercial inventory and demand-planning analysts. Its inventory features include ABC XYZ classification, safety stock, reorder levels, economic order quantity, service-level targets, and replenishment recommendations. Forecasting options include simple exponential smoothing and Holt’s trend-corrected exponential smoothing; ARIMA models remain under development. The reporting suite presents charts, tables, KPIs, inventory summaries, and recommendations, with a bot for querying analysis in natural language. Inputs can be CSV or text files, Pandas DataFrames, or data supplied through a database ETL process. The maker describes use with Pandas, Jupyter, Matplotlib, openpyxl, and xlwings. Installation is available through pip or from source, and the reporting suite can run locally with configurable host and port settings. Command examples cover Linux, Mac, and Windows. The project is licensed under BSD-3 and is free. Its maker warns that the library is in early development and unsuitable for production because its API may change.