Jorge Nguiraze is a Full-Stack Web Developer, Backend Engineer, and Database Administrator with a background in Computer Engineering from Zambeze University. He specializes in building scalable web applications, APIs, and data-driven systems that support modern digital platforms.
With over four years of experience in software development, Jorge focuses on backend architecture, system integration, and database optimization. His work includes designing secure APIs, developing robust server-side logic, and managing relational databases to ensure high performance and reliability.
Currently working at Equip Mozambique, he contributes to the development of critical systems in sectors such as ERP, agribusiness, fleet management, and healthcare. Passionate about technology and problem solving, Jorge is committed to creating efficient digital solutions that help organizations improve operations and scale their platforms.
+258 845640694
jjnguirazej@gmail.com
Maputo - Matola F
A conversational AI assistant on WhatsApp, built for the city of Beira, that democratises access to climate data and environmental education. It turns complex meteorological information into accessible, real-time guidance, helping the community prepare for extreme weather events.
Client
Start Date
Beira is one of the world's most climate-vulnerable cities. JoanaBot started from a simple question: how does weather information actually reach the people who need it most? The answer was WhatsApp, the channel almost everyone already has and knows how to use. JoanaBot is a conversational AI assistant that translates technical meteorological data into clear, actionable warnings in plain language, delivered directly inside the app the community already uses every day.
Conversational WhatsApp Interface: Access to climate information through natural conversation, with no app to install and no account to create.
Meteorological Data Translation: Technical information converted into understandable warnings and practical preparation guidance.
Real-Time Alerts: Notifications about developing adverse weather conditions, giving the community time to prepare.
Environmental Education: Educational content on climate resilience delivered conversationally and adapted to the local context.
Backend: Node with conversation state management and asynchronous message processing.
WhatsApp Integration: WhatsApp Business API with webhook handling and conversation session management.
AI Layer: Natural language processing to interpret colloquial questions and generate context-aware responses.
Data Sources: Integration with meteorological APIs for up-to-date climate data covering the Beira region.
Access Barrier Removed: By using WhatsApp rather than a dedicated app, the solution reaches users with basic phones and limited digital literacy.
Users Reached: 1300+ users interacting with the assistant.
Community Preparedness: Climate information turned into a practical preparedness tool for one of the populations most exposed to cyclones and flooding in Africa.
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