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  • Dubai, UAE

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vamssy/README.md

Vamshi

AI Engineer · Agent Systems · UAE

Building production-grade LLM applications and multi-agent systems

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Featured Projects

🔵 Aegis - Multi-Agent Financial Research System

Institutional-grade research automation for trading and analysis

An orchestrated multi-agent system that automates financial research workflows — data ingestion, semantic search over filings, signal synthesis, and structured report generation. Built with a production-first mindset: typed schemas, vectorized retrieval, and a clean dashboard UI.

Stack:LangGraphFastAPISupabase + pgvectorNext.jsPython

🟡 OpsPilot - AI Operations Assistant

Internal operations agent for SME back-office automation

An AI agent system for automating internal business workflows — task routing, document handling, and operational Q&A.

Stack:Node.jsExpressSupabaseOpenAIReact.js

🟢 Tracery - Visual Builder for RAG & LLM-Agent Pipelines

A visual workflow builder for RAG and LLM agents.

Compose an AI pipeline as a graph of typed nodes — input → retrieval → prompt → model → output — run it, inspect a per-node execution trace (I/O, latency, tokens, cost), and deploy it as a callable HTTP endpoint.

Stack:LangGraphSupabaseNode.js

Tech Stack

Languages

PythonTypeScriptJavaScript

AI / ML

LangGraphLangChainTensorFlow

Backend & Infra

FastAPINode.jsExpressSupabasePostgreSQL

Frontend

ReactNext.js

Tooling

DockerGitClaude Code

Pinned Loading

  1. aegisaegisPublic

    An orchestrated multi-agent system that automates financial research workflows

    Python

  2. opspilotopspilotPublic

    An AI agent system for automating internal business workflows like task routing, document handling, and operational Q&A.

    Python

  3. tracerytraceryPublic

    A full-stack tool to compose typed-node AI workflows on a canvas, run them, inspect a per-node execution trace, evaluate them, and deploy any workflow as a callable HTTP API

    Python

  4. SAGE-VMRSAGE-VMRPublic

    Semantic Augmentation and Gated-adapter Encoding for Video Moment Retrieval — closing the linguistic robustness gap with LLM-driven query augmentation and nested gated-adapters.

    Python