Business Transformation AI Platform "SmartOps" Now Offers AI Demand Forecasting Add-on
Defide Inc., an AI/DX consulting company, has launched a new AI demand forecasting add-on for its SmartOps platform. This feature allows businesses to predict sales, inventory, and orders by simply uploading past data, solving challenges like reliance on specific individuals, high costs, and decision delays. It enables field staff to utilize AI for predictions without specialized statistical knowledge.
📋 Article Processing Timeline
- 📰 Published: April 8, 2026 at 20:00
- 🔍 Collected: April 8, 2026 at 11:30
- 🤖 AI Analyzed: April 20, 2026 at 17:44 (294h 13m after Collected)
Defide Inc. (Minato-ku, Tokyo; Representative Director: Tetsuya Yamamoto), an AI/DX consulting company, has started offering a new add-on feature, "AI Demand Forecasting," for its business transformation AI platform "SmartOps."
This feature allows AI to autonomously analyze and predict by simply uploading past data such as sales, inventory, and orders, and immediately presents the prediction results on a chat screen. It can be utilized by field staff by simply typing "Tell me next month's demand forecast" in natural language, without requiring specialized statistical knowledge or data scientists.
### Background of Development | "Demand Forecasting" is Important, but Challenges Include Personal Dependence, High Costs, and Delays
Demand forecasting is one of the most critical management issues for optimizing inventory, reducing procurement costs, and preventing loss of opportunities, regardless of industry—manufacturing, retail, distribution, or service. However, many companies face the following challenges, and highly accurate predictions are not being effectively utilized in practice:
**Three Major Challenges Faced by the Field in "Demand Forecasting"**
* **① Personal Dependence:** Predictions managed only by specific personnel in Excel. Risk of prediction accuracy plummeting due to retirement or transfers.
* **② Wall of Expertise:** High-precision prediction model construction requires data scientists, leading to high outsourcing costs.
* **③ Decision Delay:** Time-consuming to obtain and share prediction results, missing order timing or production planning.
SmartOps' AI Demand Forecasting add-on fundamentally solves these three challenges with AI agents and a natural language interface.
### AI Demand Forecasting Add-on | Prediction Completed in 3 Steps
* **STEP 1: Upload Data**
Simply specify past data files such as sales, inventory, and orders, and the prediction model. No specialized statistical knowledge is required.
* **STEP 2: AI Agent Automates Processing**
By simply entering a natural language instruction like "Provide January sales forecast for Niiza factory," the AI autonomously performs analysis and prediction.
* **STEP 3: Instantly Utilize Prediction Results**
Prediction values, target products, and reasoning are instantly displayed on the chat screen, simultaneously enhancing decision-making speed and accuracy.
### 4 Features of AI Demand Forecasting
1. **Request predictions in natural language**
The AI agent interprets conditions and automatically executes instructions in natural language, such as "Provide sales forecasts for all products handled at Niiza factory in January." No specialized terms or operation manuals are required.
2. **Just upload data. Start with zero specialized knowledge.**
The AI automatically handles analysis to prediction by simply specifying the prediction model and data files. Field staff can immediately utilize it without knowledge of statistics or programming.
3. **Improve prediction accuracy by integrating with all SmartOps data.**
SmartOps integrates with all accumulated data to enhance prediction accuracy.
This feature allows AI to autonomously analyze and predict by simply uploading past data such as sales, inventory, and orders, and immediately presents the prediction results on a chat screen. It can be utilized by field staff by simply typing "Tell me next month's demand forecast" in natural language, without requiring specialized statistical knowledge or data scientists.
### Background of Development | "Demand Forecasting" is Important, but Challenges Include Personal Dependence, High Costs, and Delays
Demand forecasting is one of the most critical management issues for optimizing inventory, reducing procurement costs, and preventing loss of opportunities, regardless of industry—manufacturing, retail, distribution, or service. However, many companies face the following challenges, and highly accurate predictions are not being effectively utilized in practice:
**Three Major Challenges Faced by the Field in "Demand Forecasting"**
* **① Personal Dependence:** Predictions managed only by specific personnel in Excel. Risk of prediction accuracy plummeting due to retirement or transfers.
* **② Wall of Expertise:** High-precision prediction model construction requires data scientists, leading to high outsourcing costs.
* **③ Decision Delay:** Time-consuming to obtain and share prediction results, missing order timing or production planning.
SmartOps' AI Demand Forecasting add-on fundamentally solves these three challenges with AI agents and a natural language interface.
### AI Demand Forecasting Add-on | Prediction Completed in 3 Steps
* **STEP 1: Upload Data**
Simply specify past data files such as sales, inventory, and orders, and the prediction model. No specialized statistical knowledge is required.
* **STEP 2: AI Agent Automates Processing**
By simply entering a natural language instruction like "Provide January sales forecast for Niiza factory," the AI autonomously performs analysis and prediction.
* **STEP 3: Instantly Utilize Prediction Results**
Prediction values, target products, and reasoning are instantly displayed on the chat screen, simultaneously enhancing decision-making speed and accuracy.
### 4 Features of AI Demand Forecasting
1. **Request predictions in natural language**
The AI agent interprets conditions and automatically executes instructions in natural language, such as "Provide sales forecasts for all products handled at Niiza factory in January." No specialized terms or operation manuals are required.
2. **Just upload data. Start with zero specialized knowledge.**
The AI automatically handles analysis to prediction by simply specifying the prediction model and data files. Field staff can immediately utilize it without knowledge of statistics or programming.
3. **Improve prediction accuracy by integrating with all SmartOps data.**
SmartOps integrates with all accumulated data to enhance prediction accuracy.