PublishedIJFMR2025
Placeholder — your IJFMR paper title
Pravin Paithankar
One or two lines on what the paper contributes — replace from the admin portal.
PravinThe Architect
AI Software Developer · Agentic Workflows
I build agentic AI systems that ship.
Ask the RAG Waiter anything about my work — it explains the hard stuff with restaurant-grade analogies.
What I do
The Technical Architect
Agentic AI Development
Multi-step agents that plan, call enterprise tools, and verify their own work — from prototype to production.
Scalable Cloud Infrastructure
AWS + Azure architectures designed for elasticity: containers, queues, and observability from day one.
Latency Obsession
Every millisecond audited — streaming responses, warm paths, and caching until the wait disappears.
Selected work
Projects
Enterprise Agentic ChatbotFlagship
→A multi-service AI agent inside MS Teams: leaves, payslips, and ServiceNow tickets handled in plain language with full read/write/update capability.
Azure Bot ServiceMS TeamsNode.jsServiceNowHRMSAWS
The RAG Waiter (this site)
→The chat you tried above — pgvector retrieval, token-streamed answers over SSE, and every turn traced with latency + token cost to a realtime dashboard.
Next.jsSupabasepgvectorOpenAIExpress
Placeholder Project — replace me
→A short two-line pitch of another project: the problem, what you built, and the measurable result it shipped.
TypeScriptDockerPostgreSQL
Everyday tools
Node.jsTypeScriptNext.jsReactPythonOpenAI APIAgentic WorkflowsAzure Bot ServiceAWSDockerSupabasePostgreSQLpgvectorTailwind CSSCI/CD
Flagship project
Enterprise Agentic Chatbot
A multi-service AI agent living inside MS Teams: employees apply for leaves, fetch payslips, and manage ServiceNow tickets in plain language — with full read, write, and update capability.
Channel
MS Teams
Employee-facing conversational surface
Gateway
Azure Bot Service
Secure gateway, identity & message routing
Bot Framework activity▾
Agent Core
Agentic Orchestrator — Node.js (AWS)
Intent planning, tool selection, and multi-step execution. An LLM decides which enterprise tool to call, validates the result, and composes the reply.
Tool calls (read / write / update)▾
Tool
ServiceNow
Ticketing — create, query, and update incidents from chat
Tool
HRMS
Leaves & payslips — apply, check balance, fetch documents
Traces, tokens & latency▾
Telemetry
Supabase Observability
Every turn logged with token count and latency — the same pattern powering this portfolio's admin dashboard
Where I've been
Experience
2023 — Present
AI Software Developer · Your Company — replace me
Building agentic AI systems end to end: planning, tool orchestration, deployment, observability.
- —Shipped an enterprise agentic chatbot used across MS Teams
- —Cut median response latency with streaming + warm paths
2021 — 2023
Software Engineer · Previous Company — replace me
Full-stack product engineering with a focus on cloud infrastructure.
- —Led migration to containerized AWS deployments
Publications
Research
Under reviewIEEE2026
Placeholder — your IEEE submission title
Pravin Paithankar
Currently under review — update status from the admin portal once accepted.
Open source
On GitHub
Say hello
Whether it's an agentic system or a chess opening, I'm always up for a conversation.
Elsewhere