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𝗺𝘆𝗦𝗔𝗣𝟯𝟲𝟱 𝗔𝗜𝗫: 𝗧𝗵𝗲 𝗕𝘂𝗱𝗴𝗲𝘁 𝗧𝗵𝗮𝘁 𝗥𝗲𝘄𝗿𝗶𝘁𝗲𝘀 𝗜𝘁𝘀𝗲𝗹𝗳
Traditional budgets are set once and then drift for 12 months. We're replacing them with AI-driven dynamic budgeting, a living model that recalibrates itself.
How it works:
𝗘𝗥𝗣 𝗮𝘀 𝘁𝗵𝗲 𝗔𝗜 𝗯𝗮𝗰𝗸𝗯𝗼𝗻𝗲
The ERP system has evolved from being merely a record keeper to serving as an intelligent platform. Production, agronomy, labor, and cost data are shared through APIs and a unified feature store, turning static master data into real-time features for models. With bi-directional integration, predictions are not only displayed but also implemented as recommended actions.
𝗙𝗿𝗼𝗺 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘁𝗼 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝗯𝘂𝗱𝗴𝗲𝘁𝗶𝗻𝗴
Our approach treats the budget as a living model:
Gradient boosting + temporal models (LSTM / TFT). The approach treats the budget as a dynamic model: it utilizes gradient boosting combined with temporal models such as LSTM or TFT to forecast FFB yield and harvesting demand at the block level. Variance between predicted and actual production is continuously recalibrated to refine budget assumptions.
A feedback controller adjusts cost drivers like labor, transport, and fertilizer as ground truth data updates. The outcome is a rolling, self-correcting budget that accurately reflects real field conditions, rather than relying on the previous year's spreadsheet. Data (from UAV, Elios 3, UGV, and mobile capture) feed geospatial signals straight into the forecasting pipeline, grounding financial models in physical reality.
𝗧𝗵𝗲 𝗠𝗟𝗢𝗽𝘀 𝗿𝗲𝗮𝗹𝗶𝘁𝘆
None of this survives without pipeline orchestration, drift monitoring, model retraining, and human-in-the-loop validation. The magic isn't a single model; it's the data and decision architecture connecting them. The endgame isn't prediction; it's execution: where to harvest, how many workers to deploy, which blocks to intervene, and how to reallocate capital, automatically and continuously.
Magic isn't one model; it's data and decision architecture transforming perception into planning. The goal isn't prediction but execution: where to harvest, worker count, intervention blocks, and capital reallocation.
Data → Vision → Prediction → Budgeting → Action
This marks the shift from a data-driven plantation to an adaptive, self-optimizing operation.
Sjarifarudin Afa MBA
Plantation Advisor AIX
𝗺𝘆𝗦𝗔𝗣𝟯𝟲𝟱 𝗔𝗜𝗫 | AI-driven Dynamic Budget Module
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1 Agosto 2026 à 17h27
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