Manav Kaushal
[Backend Engineer | AI Systems]
I build backend infrastructure for AI systems — the kind that actually ships to production. FastAPI services, agentic pipelines, multi-tenant platforms, and the plumbing that holds them together at scale.
I build backend infrastructure for AI systems — the kind that actually ships to production. FastAPI services, agentic pipelines, multi-tenant platforms, and the plumbing that holds them together at scale.
My stack runs deep: LangGraph for orchestration, Supabase and PostgreSQL for data, Redis and Celery for async workloads, Docker for deployment. I care about observability, security, and systems that don't fall apart under pressure.
Currently focused on agentic workflows, NL-to-SQL pipelines, and platform engineering for AI-native products.
# git_commit_log
# Projects
DataLens AI
04/2025LangGraph ReAct agent for natural language analytics. Users query structured data in plain English; the agent plans, executes, and self-corrects SQL queries against a live database — returning charts, summaries, and drill-down insights without touching a dashboard.
Synthex
05/2025AI-powered educational assistant using RAG (Retrieval-Augmented Generation). Implements custom prompt chains to deconstruct complex codebases into digestible learning modules — built for developers who learn by reading source, not docs.
AI Patrolling & Bandobast System
01/2025Computer vision and NLP surveillance intelligence platform for police operations. YOLOv8n object detection at 31ms inference, crowd density analysis, anomaly detection, and a RAG pipeline with FAISS vector store — served via FastAPI with a React command center dashboard.
GrabPic
06/2026Facial recognition-powered event photo distribution. Organizers upload photos once; attendees take a selfie and get a personalized gallery in under 5 seconds.
LegalDocs
12/2024Generative AI prototype integrating Gemini APIs with RAG (Cohere embeddings) for scalable legal document analysis. FastAPI backend, LangChain orchestration, React frontend — deployed and publicly accessible.
APS-Failure Prediction
12/2024Predictive maintenance system for heavy-duty vehicle air pressure systems. 98% recall using XGBoost and SMOTE to handle extreme class imbalance — the cost of a false negative here is a breakdown on the highway.
# Training_History
AI/Backend Engineer
@ Analytics Depot05/2026 – Present
Research Intern
@ GVF08/2024 – 11/2024
BCA in Data Science
@ Jagannath Institute of Management and Science2022 – 2025