hey, Anant here

Anant Jain

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AI Systems Engineer & Full Stack Developer building intelligent agent workflows, scalable backend architectures, and high-performance automation.

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about

I’m an AI Systems Engineer and Full Stack Developer dedicated to helping businesses automate operations and scale their products. Over the last 4 years, I've specialized in building production-grade backends and intelligent AI agent workflows (using LangChain and LangGraph) that solve real business bottlenecks.

Whether it's turning database schemas into natural language chat interfaces, building automated document extraction pipelines, or optimizing high-traffic APIs, my focus is always on deliverable business value: cutting manual workloads, reducing page load times, and shipping clean, crash-proof code.

services

🤖 Custom AI & Automation

Integrating LLMs, building multi-agent planning frameworks (LangGraph), and constructing automated data analysis/SQL pipelines to replace manual overhead.

⚡ Backend & DB Optimization

Redesigning slow databases, structuring clean API models, and setting up event-driven systems (AWS SQS/Lambda) to handle millions of requests.

💻 Modern Web Applications

Crafting sleek, responsive interfaces using Next.js/React coupled with robust state management to ensure a premium user experience.

🛠️ Independent Product Delivery

Acting as a self-directed developer from idea to launch—saving you the management overhead of large agency teams.

skills
JavaScript TypeScript React.js Next.js Node.js Express.js Python FastAPI PostgreSQL MongoDB LangChain LangGraph AWS (SQS, Lambda, S3, SNS) REST APIs Git Ant Design Tailwind CSS Shadcn UI
github contributions
@anantjain341
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work experience
Jul 2023 – Present
Panchavaktra Advisory LLP
Senior Consultant (SDE-1)
  • Architected scalable REST APIs and background workers using Node.js and Python for payment verification, third-party integrations, and large file processing serving enterprise clients.
  • Built event-driven microservices pipelines using AWS SQS and Lambda, decoupling heavy background processing from API layer and eliminating request timeouts.
  • Improved backend performance by redesigning database schemas and optimizing PostgreSQL queries, achieving ~30% faster data retrieval.
  • Reduced dashboard load time from ~5s to 1.5s by redesigning backend aggregation and eliminating inefficient API chaining.
  • Reduced React re-renders by optimizing state management and Context API usage.
  • Engineered multi-agent AI assistants using LangChain and LangGraph including a natural-language-to-SQL agentic pipeline enabling non-technical users to query internal databases via chat.
  • Built OCR-based document extraction pipelines and a notification microservice for real-time system event handling across the platform.
  • Diagnosed and resolved production issues across APIs, databases, and frontend performance.
Jun 2022 – Jun 2023
Panchavaktra Advisory LLP
Consultant (SDE-1)
  • Joined the initial engineering team building enterprise SaaS platforms from scratch in a startup environment.
  • Engineered Pay-Ally, a Procure-to-Pay (P2P) platform automating procurement, invoice management, multi-level approvals, and vendor workflows for enterprise finance teams.
  • Built REST APIs with Node.js, Express.js, and PostgreSQL powering financial workflow systems.
  • Integrated ERP systems and third-party APIs enabling automated procurement and payment workflows.
  • Developed enterprise interfaces using React.js, Next.js, and Ant Design.
  • Optimized PostgreSQL queries and validated complex workflows to prevent production defects.
projects
Xcelly — Multi-Agent AI Excel Analysis
A multi-agent AI system that converts natural language queries into automated Python data analysis pipelines. Features a LangGraph orchestration architecture with Router, Supervisor, Planning, and Coding agents, real-time streaming (SSE), Excel uploads (~100k rows), and dynamic visualizations.
LangGraph LangChain FastAPI Next.js GPT-4o Pandas

The Challenge

Empowering business users to analyze large spreadsheets (~100k rows) dynamically without manual pivot tables or writing code, while keeping execution safe and sandboxed.

Architecture & Outcomes

Built a multi-agent framework orchestration in LangGraph. Features streaming responses via SSE, background pandas data execution, and rich visual plots.

100k+ Rows Loaded
5+ LLM Agents
Source ↗ Live ↗
Restaurant RPS — Resource Planning System
An AI-powered forecasting system predicting hourly customer covers, staffing requirements, and ingredient procurement costs based on date and weather conditions. Features a self-learning correction engine that incorporates manager feedback and continuously improves forecast accuracy.
FastAPI Next.js 14 SQLAlchemy Tailwind CSS Recharts Python TypeScript

The Challenge

Predicting staffing and inventory requirements dynamically under varying weather and calendar conditions, while continuously adapting predictions based on manager feedback.

Architecture & Outcomes

Built using FastAPI and Next.js. Features a self-learning correction engine that updates coefficients adaptively based on real execution feedback, with MAE-based accuracy tracking visualized via Recharts.

Adaptive Engine
MAE Accuracy Tracking
Source ↗ Live ↗
contact
AJ

Let's discuss your project

Need custom AI automation, a faster backend, or help shipping a new SaaS feature?
Reach out to discuss how we can build a high-performance solution for your business.

anantjain341@gmail.com