Arjun
Vankani
I design and ship multi-agent AI systems — LLM agents that route intent, retrieve knowledge, query databases, and act autonomously in production. 2+ years across Agentic AI, RAG, Computer Vision, and NLP, from research labs to live marketing platforms.
About
I'm an AI Engineer building production-grade agentic systems — from a multi-agent "Super Agent" that routes marketing queries across specialized sub-agents, to RAG pipelines backed by vector search, to research on person re-identification and haze removal for surveillance video. I care about systems that don't just generate text, but reliably retrieve, decide, and act.
Currently shipping agent infrastructure at OpinionAds in Ahmedabad, and previously trained 100+ learners in AI/ML as a Master Trainer for SAP's Code Unnati program.
Capability modules
Agents & Orchestration
LLMs & RAG
Embeddings & Vector Search
Computer Vision
Cloud & Backend
Languages & Frameworks
Experience
- Architected a multi-agent Super Agent that routes user requests across specialized AI agents based on intent, reducing manual query handling.
- Built a RAG Agent on a pgvector-backed Aurora PostgreSQL pipeline for accurate, context-aware business responses.
- Built a SQL Agent translating natural language into queries, letting marketing teams self-serve insights without SQL knowledge.
- Designed evaluation & guardrail mechanisms to catch hallucinations and ensure reliable LLM output in production.
- Delivered AI/ML sessions under the SAP-sponsored Code Unnati Program, covering Power BI, SAP, ML and Deep Learning.
- Built an OCR pipeline for automated data extraction from images.
- Contributed to election analysis (CSDS/Lokniti) and food-security analysis (IFPRI, Sri Lanka) projects.
- Researched person re-identification under same-clothing conditions (GUJCOST project).
- Developed haze removal techniques for a DST-funded research project.
- Built NLP models for Indic languages and deployed via Docker + FastAPI for voice/chat bots.
Projects
00 semantic-image-search-clip/ text-to-image retrieval via CLIP embeddings independent 2025 ›
Text-to-image retrieval system enabling search across both global datasets and local folders — queried via CLI.
01 comfyui-n8n-automation/ CSV-driven creative workflow orchestration independent 2025 ›
Automates image generation, video generation, upscaling, and segmentation through seamless HTTP-based integration.
02 environmental-ai-toolkit/ multi-modal text + image analysis toolkit independent 2025 ›
Sentiment analysis, NER, fill-in-the-blank, and QA alongside classification, detection, segmentation, and image generation.
03 llamaweb/ fine-tuned LLaMA + RAG over documents research 2024 ›
Fine-tuned LLaMA for domain-specific knowledge retrieval, evaluated using BLEU score against reference answers.
04 person-reidentification/ tracking + re-ID for surveillance video research 2023 ›
Object identification and tracking via CNNs and Deep SORT, with a FaceNet model for facial-feature accuracy.
05 haze-removal/ U-Net dehazing benchmarked vs. 4 methods research 2023 ›
Synthesized hazy images using beta and airlight parameters to validate removal quality before re-identification.