buffers.ai vs supplychainpy
buffers.ai
buffers.aisupplychainpy
supplychainpy.orgSide by side
| Figure | buffers.ai | supplychainpy |
|---|---|---|
| Price from | $25/mo | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 8 | 1 |
| Spec score · Inventory Optimization Software | 7.6 (#7) | 7.9 (#3) |
| Forecasting | Forecasting backtests TimesFM, LightGBM, Prophet, Exponential Smoothing, and Moving Average over a rolling six-month window and selects a champion model per SKU. | The features page lists simple exponential smoothing and Holt’s trend corrected exponential smoothing; ARIMA models are marked as under development. |
| Founded | 2015 | 2016 |
| Input data | The minimum input is one row per SKU per day with date, SKU identifier, and units sold; CSV or XLSX uploads can be used for a benchmark without ERP work. | The project describes using CSV or text files and data from a database through a data API or ORM such as SQLAlchemy. |
| Integrations | Production integrations use recurring batch feeds configured for the customer’s stack; FTP-based ERP exchange has been used, and the maker publishes no list of named pre-built ERP or POS connectors. | The maker describes use with Pandas, Jupyter, Matplotlib, openpyxl and xlwings. |
| Target users | Replenishment is designed for replenishment, allocation, and merchandising teams shipping from a central warehouse to store chains, as well as store managers. | The project describes itself as a decision-support tool for analysts in commercial inventory and demand-planning roles. |
Plans
buffers.ai
- Replenishment — stores 61+$25 a month
- Replenishment — stores 31–60$75 a month
- Replenishment — stores 11–30$125 a month
- Replenishment — stores 1–10$175 a month
- Purchasing — up to 1,000 SKUs$2,000 a month
- Purchasing — up to 6,000 SKUs$3,000 a month
- Implementation/setup$5,000, paid once
- Purchasing — more than 6,000 SKUs$10,000 a month
In their own words
buffers.ai
buffers.ai is a web service for retail and manufacturing enterprises that automates demand forecasting, purchase planning, and inventory replenishment. Forecasting backtests TimesFM, LightGBM, Prophet, Exponential Smoothing, and Moving Average over a rolling six-month window, selecting a champion model for each SKU. Buy Plan creates a 12-month purchasing plan by category and month, in units and dollars, from a buying budget, including when sales history is absent. Replenishment recalculates each product’s target stock at every store daily and supports assortment, launches, promotions, and allocation across online, store, and wholesale channels. Production integrations use recurring batch feeds configured for a customer’s stack; CSV or XLSX uploads can support a benchmark without ERP work. The service uses HTTPS/TLS for the product and benchmark flow. Pricing starts at $25 a month for the 61+ store marginal plan, while other plans and possible setup fees vary by scope and scale.
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.