In Vietnam, digital transformation in agriculture is progressing rapidly — yet many farmers still struggle with complex paperwork, manual record-keeping, and limited access to transparent production data. Recognizing this gap, the DIG-AgriTech project set out to integrate Generative AI into an AgriTech mobile application to enhance user experience, especially for cooperative members and farmers.

The vision is to create an intelligent digital platform that simplifies production management, improves traceability, accelerates label and certification processes, and strengthens data-driven reporting. Over time, the app aims to serve as a reliable ecosystem that connects farmers, cooperatives, and regulatory authorities — promoting sustainable production while increasing the market value of agricultural products.

Project Overview

Challenges

Supporting farmers requires a deep understanding of real-world constraints and operational habits. The primary challenges included:

1. Data Input Complexity
   Farmers often struggle with manual data entry on mobile devices due to low digital literacy and inconsistent internet access.

2. Voice-Based Interaction Needs
   The application receives data mainly through voice input. This requires:
   • High speech recognition accuracy
   • Support for diverse local dialects and accents
   • Noise-handling in outdoor farm environments

3. Intent Understanding
   Even after transcribing speech correctly, the system must accurately interpret meaning:
   • What task does the farmer want to perform?
   • Is the user reporting harvest quantity, requesting label issuance, or inputting fertilizer usage?

4. Traceability and Reporting Requirements
   Agricultural production involves multiple compliance steps. The system must ensure:
   • Transparent and verified traceability data
   • Automatic and accurate reporting for management authorities

Solution Approach

DIG-AgriTech leveraged modern GenAI technologies to address these real-world requirements:

AI-Enhanced Voice Processing

• Integration of advanced speech-to-text engines trained on Vietnamese agricultural terminology
• Regional accent tuning for improved comprehension and personalized user experience

Intelligent Intent Recognition

• LangChain-powered conversational logic
• Natural language understanding models detect user intent and trigger appropriate workflows
• Context retention to support multi-step farm management tasks

Automated Data Structuring & Validation

• AI converts unstructured voice input into standardized production logs
• Consistent data for traceability, certification, and compliance submissions

Seamless Workflow Automation

• Using Dify & N8n to automate:
  • Traceability record updates
  • Stamp/label application processes
  • Report generation and statistical dashboards

Key Expected Outcomes

Long-Term Vision

The app is designed not just as a digital tool, but as a trusted agricultural platform — one that connects:

• Farmers
• Cooperatives
• Government & regulatory bodies
• Value chain stakeholders

Ultimately, DIG-AgriTech aims to accelerate Vietnam’s agricultural digital transformation, fostering:

• Sustainable production
  Higher economic value for local produce
  Stronger farmer empowerment through technology

Conclusion

DIG-AgriTech demonstrates how Generative AI can transform traditional agriculture by simplifying complex processes and enabling farmers to effortlessly manage production. Through smart automation, voice-driven interaction, and transparent traceability, the platform positions itself as a pioneering solution in the AgriTech space — driving both digital inclusion and sustainable growth.