I build AI-powered applications that go beyond chatbot wrappers. Whether you need computer vision, conversational AI, voice synthesis, NLP, recommendation engines, or vector-based memory systems, I architect the AI layer as a core product feature from day one.

LLM-powered apps: OpenAI GPT, Claude, Gemini integration with context-aware prompting, persistent memory (pgvector), and multi-turn conversation management

Computer vision: On-device inference with TensorFlow Lite, face detection and segmentation with OpenCV, server-side analysis with AWS Rekognition

Voice AI: Real-time voice synthesis with ElevenLabs, WebRTC voice chat infrastructure

NLP features: Contextual text generation, sentiment analysis, content moderation pipelines

Recommendation engines: Collaborative filtering, behavioral learning, personality-based matching algorithms

Scope and architecture: We define the AI features, data pipeline, model selection, and infrastructure

Backend development: Node.js APIs, database design (PostgreSQL, MongoDB, Firebase), cloud infrastructure (AWS)

AI integration: Model integration, inference optimization (on-device when possible for speed and privacy), fallback strategies

Frontend: React or React Native UI built around the AI features

Testing and deployment: End-to-end testing, performance optimization, App Store / web deployment

Every AI feature I build ships inside a real product with real users. I've delivered AI apps across health-tech (skincare scanner with on-device CV), fitness (AI coaching with voice guidance), dating (NLP matching + voice chat), and SaaS (multi-model AI chat platform).

If you're building an AI-powered product and need someone who handles the full stack, not just the prompt engineering, let's talk.

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