Kaicho

Key Skills

Software

Label Studio

Roboflow

Internal/Proprietary Tooling

Top Subject Matter

Agricultural disease diagnosis (AgriTech/plant pathology)

AgriTech data (soils, crops, pesticides) and ML dataset preparation

Top Data Types

Image

Text

Top Task Types

Object Detection

Polygon

Bounding Box

Segmentation

Classification

Fine-tuning

Data Collection

Text Generation

Freelancer Overview

EcoGrow AI — Agricultural Disease Diagnosis Platform (Founder & Lead Developer). Brings 15+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Diploma / Certificate in Hospitality Management, Tanzania Institute of Tourism and OPERA PMS Advanced Certification, Oracle Hospitality. AI-training focus includes data types such as Image and Text and labeling workflows including Object Detection and Data Collection.

Labeling Experience

Zanzibar Farm Intelligence System — Data & Knowledge Base (Independent Developer)

TextData Collection

Created a structured agricultural database intended to support machine-learning training and knowledge-driven inference for Tanzania and Zanzibar. Compiled Zanzibar crop profiles (e.g., cloves, vanilla, seaweed, cassava, rice) and linked them with pesticide registry information. Built ML training pipelines to prepare datasets for future model development and third-party licensing. • Soil type and crop profile compilation • Pesticide registry integration • Dataset preparation for ML pipelines • Curated knowledge base for licensing to NGOs/companies/ministry

2024 - Present

EcoGrow AI — Agricultural Disease Diagnosis Platform (Founder & Lead Developer)

ImageObject Detection

Developed an on-device plant disease diagnosis AI system for East African farmers, incorporating YOLO-style object detection workflows to interpret plant imagery. Integrated Google Gemini Vision and deep learning models (PyTorch/TensorFlow, MobileNet, and crop-specific training) to produce diagnosis outputs for Zanzibar crop varieties. The work involved assembling Zanzibar-specific training material and preparing it for model learning and evaluation. • Crop/plant imagery used for disease recognition • Model training using Zanzibar-specific crop varieties • Diagnosis output generation for end-user decisions • System iteration for production-grade performance

2024 - Present

Education

Work History