This is a proposal for the Redis AI Challenge Beyond the Cache. I present MindMirror, an innovative mental health analysis platform that uses RedisAI to perform real-time psychological assessments and deliver actionable results in under 200 ms.
What I built: MindMirror processes user inputs to identify dominant psychological archetypes among 7 distinct profiles, generate dynamic 3D brain visualizations, track emotional states using multidimensional mood state vectors, and analyze temporal patterns in mental states. Redis transforms from a simple cache to an AI inference engine capable of processing natural language, storing psychological vectors, and returning real-time insights.
Demo and code: https://youtu.be/YWSW3bBuIBU and https://github.com/LooneyRichie/Mind-Mirror
How I used Redis 8: RedisAI acts as a real-time inference engine to convert text into emotional vectors and run vector similarity models. Mood state dimensions are stored as RedisAI tensors with floating-point precision and retrieved on the fly for archetype matching calculations and neural visualization.
Psychological vector storage: each user has a mood state tensor with multiple dimensions representing emotional parameters. Real-time retrieval and analysis allow calculating archetype scores and feeding 3D visualizations and AI agents that suggest interventions.
Multi-model architecture: use of Redis Streams for real-time session tracking, RedisJSON for storing structured insights, RedisTimeSeries for analyzing temporal evolution and detecting anomalies, and RedisAI for vector matching and future deployment of ONNX or TensorFlow models.
Example of temporal analysis: emotional coherence per user is recorded in a time series; this allows aggregating by day, detecting atypical peaks, and generating alerts for clinical follow-up or personalized recommendations.
Archetype matching and semantic search: text indexes allow mapping free inputs to keyword patterns and associated scores. The search engine identifies relevant archetypes from word combinations and score thresholds, facilitating the detection of multiple profiles in a single session.
Summarized technical architecture: user interface in Streamlit or similar, vector processing with RedisAI, archetype matching engine with RedisSearch, insight persistence with RedisJSON, temporal analysis with RedisTimeSeries, and 3D visualization layer for neural mapping.
Key features powered by Redis: real-time mood vectorization with 8 dimensions, multi-archetype detection based on more than 1000 word patterns, temporal analysis and anomaly detection between sessions, and neural visualizations derived from psychological vectors. Observable performance: response times reduced from approximately 650 ms to 190 ms, increased session concurrency, and lower memory usage when RedisAI is properly integrated.
How to get started: clone the repository https://github.com/looneyrichie/mindmirror and run the startup script to deploy RedisAI and the interface. Roadmap: deploy ONNX models via RedisAI, implement cross-session analysis to detect longitudinal patterns, add a recommendation engine powered by Redis, and build an archetype relationship graph with RedisGraph.
About Q2BSTUDIO: Q2BSTUDIO is a software development company specializing in custom applications and custom software, with experience in artificial intelligence, cybersecurity, and AWS and Azure cloud services. We offer business intelligence services, AI solutions for companies, custom AI agents, and Power BI developments for visualization and decision-making. Our team designs custom applications that integrate machine learning models, secure architectures, and scalable cloud deployments to drive the digital transformation of clients across multiple sectors.
Featured Q2BSTUDIO services: custom software development, integration of artificial intelligence into business processes, cybersecurity audits and solutions, deployment and operation on AWS and Azure cloud services, business intelligence projects with Power BI, and AI agents for automation and advanced assistance. Relevant keywords for positioning: custom applications, custom software, artificial intelligence, cybersecurity, AWS and Azure cloud services, business intelligence services, AI for companies, AI agents, Power BI.
Author and contact: Richie Looney, creator of MindMirror. Q2BSTUDIO collaborates on AI and security projects and is open to new work and collaboration opportunities. If you would like more information about custom integrations, artificial intelligence solutions, or cloud services, contact our team to design a custom enterprise solution.
