Pratham Mande
@prathammande
I build LSTM/XGBoost forecasting and RAG-based AI systems with FastAPI microservices and agent workflows.
IndiaWhat I'm looking for
I’ve built a hybrid VM workload forecasting system using LSTM for workload prediction and XGBoost for VM recommendation, plus synthetic datasets to keep time-series analysis reliable.
I also create LLM pipelines like a stock RAG system with real-time API retrieval and a multi-agent “micro-fintech” agent using A2A and MCP, wrapped in FastAPI and designed for async routing and risk analysis.
Experience
Work history, roles, and key accomplishments
Cloudy - VM Forecasting
Personal Project
Built a hybrid system using LSTM for workload forecasting and XGBoost for VM recommendation, achieving 92.4% recommendation accuracy.
Fagent - Micro-Fintech Agent
Personal Project
Built a distributed multi-agent system using A2A and MCP protocols for budget routing and financial risk analysis.
Education
Degrees, certifications, and relevant coursework
Laxmi Narain College of Technology and Science
Bachelor of Technology, Computer Science
2022 - 2026
Grade: 7.76 CGPA
Bachelor of Technology in Computer Science with specialization in Artificial Intelligence and Machine Learning, achieving a CGPA of 7.76.
Sagar Public School
Senior Secondary, Science
2021 - 2022
Grade: 75%
Completed senior secondary education with PCM as core branch, achieving 75%.
Tech stack
Software and tools used professionally
Availability
Location
IndiaAuthorized to work in
Job categories
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