LENS ā AI Image Intelligence
A multimodal AI system that transforms images into contextual narratives, analysis, and creative interpretations.
Problem
Most image analysis tools provide static or generic outputs without contextual adaptability. Users lack interactive, real-time, and mode-specific interpretations of visual data.
Solution
Implemented mode-conditioned prompting to dynamically control output style (storytelling, roast, detective, documentary)
Built a secure Next.js API layer to handle multimodal inference without exposing API keys
Enabled streaming responses (SSE) for real-time token generation and improved UX
Optimized prompt engineering for consistent tone and contextual accuracy across modes
Tech Stack
GPT-4o VisionNext.jsStreaming (SSE)Multimodal AI
Architecture
Image Input ā Prompt Conditioning ā Vision Encoding ā Multimodal LLM Inference ā Token Streaming (SSE) ā Live UI Rendering
Challenges
Handling multimodal reasoning required careful prompt design to balance creativity and accuracy. Streaming responses introduced complexity in UI rendering and state management, while maintaining low latency for real-time interaction.
What Iād Improve Next
- ā¢ Add fine-tuned vision models for domain-specific analysis
- ā¢ Introduce caching for repeated image queries
- ā¢ Optimize latency using edge inference or model distillation