AI-powered mobile app for real-time robotic fleet control

Built a Bluetooth-connected mobile app that fuses AI and manual control, enabling van operators to manage robotic systems in real time—handling both continuous sensor streams and bursty high-volume data, all within a secure local network.

Modular AI pipeline for in-van perception, planning, diagnostics

Designed a modular, parallel-processing pipeline that routes in-van data to specialized AI models for perception (e.g., dimension/text recognition), motion planning, damage detection, packing optimization, and fleet diagnostics—deployable on both local hardware and cloud.

AI-driven UI for real-time delivery guidance and optimization

Delivered an adaptive UI component that provides real-time, AI-generated guidance to delivery personnel, optimizing package retrieval and handoff with dynamic instruction flows.

AI system for in-van/cloud use, piloting with global fleets

Engineered the system for dual deployment (in-van and cloud), with secure processing and resilient offline support—now in pilot phase for rollout with major global delivery fleets.

Scalable, real-time AI pipeline to protect temperature-sensitive goods globally

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Deployed a real-time IoT data pipeline that ingests terabytes of temperature, location, and handling events, then uses event-driven AI agents to flag anomalies and push instant alerts—helping prevent the $30 B annual loss of temperature-sensitive goods.

On-device AI to autonomously maintain safe medicine temperatures in real time

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Designed an on-device AI algorithm that continuously tunes set-points in response to ambient conditions, removing the need for human intervention and ensuring medicines and vaccines stay within safe ranges in the field.

AI-powered compliance & audit engine with policy alerts, end-to-end traceability

Built a policy-based alert engine and automated, AI-driven audit report generator that produces secure, end-to-end traceability logs—dramatically cutting manual data-gathering time for regulatory reviews.

Secure data pipeline with ongoing maintenance, processing terabytes daily

Implemented encrypted network tunnels, Bluetooth/Wi-Fi auto-reconnect mobile apps, and fault-tolerant cloud infrastructure to process tens of terabytes per day, with Plank providing ongoing maintenance and uptime assurance.

AI-powered procurement research copilot

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Built a domain-specific AI agent system fine-tuned on battery chemistries, vendor catalogs, and robotics specs—enabling procurement teams to explore, compare, and source equipment with precision.

Autonomous vendor workflow automation

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Replaced manual procurement steps (email, fax, RFPs) with a multi-agent system that autonomously handles vendor inquiries, negotiations, and evaluations—learning from prior transactions to improve over time.

Scalable AI-powered crawler indexing terabytes of equipment data

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Engineered a smart crawling and indexing pipeline to fetch and deduplicate tens of terabytes of equipment data, ensuring a continuously updated knowledge base with minimal manual upkeep.

AI classification engine to auto-classify SKUs

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Developed an AI system that classifies equipment and SKUs using semantic embeddings and unsupervised topic modeling—creating a unified schema across diverse product types without hand-labeled categories.

Multi-agent graph-based AI agents analyzing financial data to deliver insights

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Built ~10 interoperating graph-based AI agents that automatically ingest, categorize, and analyze transactions from all connected financial institutions, surfacing tailored insights such as spending trends, budgeting nudges, and savings opportunities.

AI memory system for personalized financial advice from behavior data

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Developed a persistent vector-based memory system that captures financial behavior and user interactions, enabling agents to infer preferences, habits, and life context—powering deeply personalized financial advice.

AI-curated financial news feed

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Delivered an embeddings-powered indexing and ranking engine that classifies trending news and matches it to individual users' financial interests and holdings—creating a personalized Bloomberg-like dashboard.

AI platform with autoscaling, real-time inference, and regulatory security

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Designed a high-throughput system with dynamic autoscaling, secure hybrid deployment (cloud + on-prem), and real-time inference—paired with ongoing operational support and regulatory-grade data protection.

AI agent system to auto-create MLS listing videos in seconds

Built a multi-agent graph system that assembles MLS photos, clips, audio, and text into polished listing videos in < 5 s on GPU clusters, then auto-publishes to agents’ social  channels.

AI crawler unifying real estate data from Zillow, MLS, agents

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Developed an AI crawler that pulls images and metadata from agent sites, MLS, Zillow, and Redfin, cleans and deduplicates them, and unifies everything into a common schema for seamless editing.

AI tool for agents to auto-generate branded video content

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Delivered an AI-driven template framework letting agents swap fonts, backdrops, marketing copy, and property details to produce highly personalized videos that match their brand style.

Scalable AI system managing 1M+ listings, with ongoing maintenance

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Handles ~1 M listings with isolated databases for each brokerage, plus ongoing maintenance—already live with Sotheby’s agents.

AI engine to help businesses select optimal new store locations nationwide

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Built a multi-dimensional regression tree model trained on US census, cellular, and ordering data to score millions of intersections and recommend optimal store locations—used by major retail and restaurant chains nationwide.

High-performance AI-enabled geospatial visualization

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Delivered an SSE-based web map UI that streams server-rendered tiles and uses an AI model to reduce rendering load by intelligently narrowing the set of relevant intersections based on user input.

Real-time AI pipeline for nationwide sales and demographic analysis

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Engineered a concurrent data processing pipeline capable of re-running nationwide analyses in real time as users tweak parameters, handling massive datasets across geography, demographics, and sales history.

AI model orchestrator using LLMs to auto-select best algorithms

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Built a model orchestration system using LLM-judging to auto-select the best fit across regression, random forest, and graph-based models - also supporting ensembling for more accurate recommendations.

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Scalable RAG AI answering dev queries from 100TB/day data

Built a RAG pipeline that ingests GitHub code, Linear tickets, Slack threads, specs, and more into Pinecone + Postgres, then powers an AI chatbot that answers how-to, debugging, and code-review queries—scaling to 100 TB/day with 1,000 + elastic workers and thousands of live webhooks.

LLM-powered Next.js library for real-time, context-aware engineering answers

‍Delivered a Next.js library that streams LLM responses and auto-renders the right component - plain text, code blocks, flowcharts, architecture diagrams, or performance charts - giving engineers rich, context-aware answers in real time.

Automated product planning from PRD to code with ticketing and reviews

Converted product requirements into draft design docs and populated Linear boards with ticket hierarchies, then checked pull requests for spec compliance—automating the planning loop from PRD to code.

SOC-2/HIPAA-compliant, 1-click AWS deployable stack & ongoing maintenance

Packaged the stack as Terraform for one-click AWS deployment, met SOC-2 & HIPAA via least-access controls and Vanta monitoring, and provided ongoing maintenance across multiple enterprise installations.

Secure SDKs and AI shopping agent built using AITP protocol

Delivered Typescript + Python SDKs that implement the new AITP protocol and a demo e-commerce agent that lets users shop Amazon directly from any MCP-compatible chat UI—built with clean architecture, 100 % test coverage, and penetration-tested for production-grade security.

Automated scalable AWS backend

Delivered infrastructure-as-code scripts to provision and auto-scale a microservice backend on AWS, including support for Trusted Execution Environments (TEEs)—a complex requirement rarely supported in cloud-native stacks.

AI-powered code generator that auto-deploys error-free code from specs

Created a multi-agent generator that ingests the AITP spec and outputs a fully functional, self-deploying agent codebase, automatically detecting and fixing type, compile, and runtime errors.

Ongoing end-to-end maintenance and security ops

Handled end-to-end maintenance, community triage, and vulnerability patching for Near’s open-source projects, ensuring long-term sustainability and developer trust.