This milestone focuses on the design, development, and deployment of a Minimum Viable Product (MVP) of FriendnPal’s neuro-symbolic AI mental health assistant. The goal is to create a hybrid AI model that combines deep learning’s conversational abilities with symbolic reasoning for context awareness and personalized care. This milestone includes recruiting additional AI and NLP engineers, refining the knowledge graph, building multilingual support modules, and integrating predictive mental health features such as suicide risk flagging and emotional state analysis. It will also cover backend infrastructure, ethics and privacy safeguards, and initial user testing in three communities across Nigeria.

MVP version of FriendnPal AI assistant with neuro-symbolic architecture. Working multilingual chatbot (English, Hausa, Swahili, Yoruba, Pidgin) with emotional intelligence capability. Backend infrastructure deployed and tested for performance, security, and scalability. Personalized responses. Predictive mental health scoring model tested on anonymized data for accuracy and sensitivity. Ethics review and documentation for transparency and accountability. Field test report and analytics from pilot groups in underserved communities.

$80,000 USD

Working MVP capable of engaging in context-aware, empathetic mental health conversations. 90%+ uptime in chatbot deployment across selected test platforms. User satisfaction rating of at least 80% in pilot feedback forms. Accurate prediction (70%+ precision/recall) of high-risk user messages (e.g., suicidal ideation, emotional distress). System handles at least 1,000 concurrent users with latency under 1s. MeTTa-powered reasoning model generates at least 3 distinct therapeutic response paths per session. 3 comprehensive test reports (one per target community) with usability and cultural fit analysis.