One AI system connecting context, retrieval, memory, and delivery governance.
I worked across engineering and project delivery for relationship and emotional-support scenarios, building AI application services while keeping scope, risk, quality, and cost under control.
Moor.AI focuses on relationship communication and emotional support, connecting voice and text conversations, personal context, relationship records, long-term memory, emotional insight, communication guidance, and mindfulness tools into a continuous companion experience.
I worked on Java / Spring services, multiple AI integrations, RAG, dynamic context, long-term memory, Redis, RabbitMQ, APIs, and data security, while also advancing scope, decomposition, dependencies, risks, quality, cross-functional coordination, performance, cost, and reliability.
Business APIs and multi-AI integration
Retrieval, dynamic context, and long-term memory
Caching, messaging, and business coordination
Scope, dependencies, risks, and acceptance
Explore the relationships between input, context, model services, and supporting capabilities.
RAG and long-term memory / Cache and async tasks
Start with the user’s input and conversation state, establishing clear business interfaces and error semantics.
An engineering illustration of the business and technical relationships in the project.