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LFGHcoder/README.md

Lakshya Pandey

Computer Science student focused on AI-driven automation systems, backend engineering, and data pipelines.

I build systems that combine LLMs, structured workflows, and scalable APIs to solve real-world problems.


Selected Projects

Project Description Tech
Prospect Intelligence Engine AI-powered lead intelligence system that processes and ranks business prospects using web scraping, deterministic scoring, and structured outputs (HOT/WARM/LOW) Python · Data Pipelines · Automation
NovaOps Agent Multi-agent AI system that automates recruiting workflows using coordinated agents for screening, interview simulation, and evaluation Python · AWS Bedrock · LLMs
Alvora AI Full-stack AI career platform with LLM-powered resume analysis and personalized learning paths, deployed on AWS FastAPI · React · PostgreSQL
Sales Outreach AI Agent AI-driven outreach system with async pipelines, sentiment tagging, and analytics, used by 30+ users FastAPI · OpenAI API · Backend Systems

Technical Stack

Languages: Python · Java · C++ · JavaScript · SQL

Frameworks: FastAPI · React · Node.js

AI / ML: OpenAI API · LangChain · PyTorch · TensorFlow

Tools & Cloud: AWS · Docker · PostgreSQL · Selenium · CI/CD


Current Focus

  • Designing scalable backend systems
  • Building multi-agent AI workflows
  • Developing production-ready automation pipelines

Contact

LinkedIn: https://www.linkedin.com/in/lakshya-pandey-
Email: [email protected]

Pinned Loading

  1. NovaOps-Agent NovaOps-Agent Public

    Multi-agent AI system that automates recruiting workflows using Amazon Nova for resume screening, interview planning, and candidate evaluation.

    Python

  2. Prospect-Intelligence-Engine Prospect-Intelligence-Engine Public

    AI-powered lead intelligence system that identifies and ranks high-value business prospects using web scraping, deterministic scoring, and structured data pipelines.

    JavaScript

  3. research-validator research-validator Public

    FastAPI-based research validation API that extracts factual claims, searches for supporting evidence, and scores credibility using web data and optional OpenAI embeddings.

    Python