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buffers.ai vs supplychainpy

buffers.ai

6.1#6 in inventory optimization softwareFrom $25 a month
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supplychainpy

6.4#4 in inventory optimization softwareFree plan
Free planAPILinuxmacOSSelf-hosted
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What both publish

Factbuffers.aisupplychainpy
ForecastingForecasting 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.
Founded20152016
Input dataThe 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.
IntegrationsProduction 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 usersReplenishment 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.

buffers.ai plans

  • 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

supplychainpy plans

  • supplychainpy 0.0.5Free

Pick buffers.ai if…

buffers.ai is aimed at retail and manufacturing enterprises, including replenishment, allocation, and merchandising teams serving store chains from a central warehouse, as well as store managers.

Pick supplychainpy if…

supplychainpy suits analysts working in commercial inventory and demand planning who want a Python-based decision-support tool. It is also relevant to users working with Pandas DataFrames, CSV or text files, or database-supplied data.

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