• Role: Builder — AI & Data Systems
• Education: BITS Pilani, Goa → University at Buffalo (2+2) · B.E. EEE
• Building: Closr
• Focus: Agents · Orchestration · Inference cost · Workflows
• Mantra: Build things that save you money, compute, and time.
• Creative problem solving under resource constraints

Fully autonomous B2B lead generation pipeline built for the creator economy, engineered to run entirely on local hardware (4GB VRAM RTX 3050). Scrapes 7 high-intent web sources and processes the DOM through a 4-stage Extraction Fortress (using CPU-bound bart-large-mnli and all-MiniLM-L6-v2) to aggressively filter noise before a single token touches the GPU. Extracts entities via qwen2.5:7b (Ollama) and routes them through a concurrent 5-thread ReAct Agent state-machine for waterfall email enrichment—maintaining strict $0 cloud LLM costs.

Palantir-grade intelligence pipeline that scrapes and structures geopolitical data into a Neo4j knowledge graph. Engineered a 2-Layer Resolution Gauntlet using fuzzy matching and all-MiniLM-L6-v2 vector cosine-similarity to disambiguate entities. The entire inference engine is memory-optimized to run within a strict 4GB VRAM ceiling via dynamic context reduction and a rolling keep-alive window.

Secure event ticketing ecosystem that eliminates fraud using TOTP (Time-based One-Time Password) entry mechanisms with 30-second refresh cycles. Implements resale intelligence and smart-contract royalties to track and verify all legitimate ticket transfers. Live on Vercel.

A localized data intelligence platform translating real-world geo-signals into actionable business strategy. Developed a map-based analytics interface using Leaflet, MapTiler, and OpenRouteService. Halted post-prototyping after validating a lack of product-market fit—demonstrating a strict focus on building systems with real business ROI.

Languages:

AI / Data:

Infra / Deployment:

"The best systems are the ones you never notice — because they just work."