I build AI-powered systems, distributed infrastructure, and products that interact with the real world — from edge AI and computer vision to spatial computing, real-time systems, and production backends.
Research → Architecture → Build → Measure → Ship
- 4+
- Years shipping production systems
- 500K+
- Events/day on platforms I’ve built
- 44%
- Faster deploys after CI/CD rebuild
Selected Work
Nightwatch
AI video intelligence at the edge
Motion-gated edge pipeline that turns CCTV feeds into real events — YOLO and Gemini Vision run on-premises, so only event payloads and snapshots leave the building.
Spatial
Deterministic spatial computing infrastructure
A sensor-agnostic foundation for perception and physical-world interfaces — typed world model, replaceable device adapters, running on nothing more than a webcam and a projector.
Streamshort
Video infrastructure + creator monetization
Go backend for short-form video streaming — uploads, HLS delivery over CloudFront, subscriptions and creator payouts, deployed with a full CI/CD pipeline on AWS App Runner.
Influenzer
Creator × brand marketplace
Clean-architecture Go service behind a B2B creator marketplace — campaigns, proposals, real-time messaging, and a Razorpay escrow/wallet system underneath.
Other experiments
Research
Edge AI for Real-Time Video Intelligence
Can motion-gated edge detection cut the cost and latency of multimodal video AI without losing accuracy? Nightwatch's pipeline runs cheap local detection first and only escalates to Gemini Vision when something actually moves — instead of sending every frame straight to a multimodal model.
Measuring: Latency · Cost · Bandwidth · Accuracy
How I Build
I prefer difficult problems over fashionable technologies. I start with the problem, research the constraints, build the smallest useful system, measure it, and iterate.
Problem → Research → Architecture → Prototype → Measure → Ship
Experience
Mar 2026 — Present
Own the analytics platform end to end — event ingestion, SDK, real-time dashboards — processing 500K+ events/day, plus LangChain/RAG agents that cut manual design time 60%.
Python · LangChain · RAG · AWS · Kafka
Aug 2022 — Feb 2026
Led the migration of a monolith to microservices across 5+ service teams, cut deployment time 44% with Docker/Jenkins, and held 90%+ unit test coverage across releases.
Python · Flask · Kafka · GraphQL · Kubernetes · AWS ECS
Currently Exploring
AI Agents
Reliable tool use, evaluation, memory and orchestration.
Edge AI
Running intelligence closer to physical data sources.
Spatial Computing
Sensors, perception, world models and physical interfaces.
Distributed Systems
Reliability, event-driven architecture and real-time infrastructure.
Stack
Building something technically difficult?
I'm interested in AI infrastructure, intelligent systems, spatial computing, distributed systems and ambitious early-stage products.
Let's talk →