Suparna M.

𝐄𝐗𝐏𝐄𝐑𝐓 𝐁𝐀𝐂𝐊𝐄𝐍𝐃 & 𝐀𝐈 𝐄𝐍𝐆𝐈𝐍𝐄𝐄𝐑 𝐒𝐏𝐄𝐂𝐈𝐀𝐋𝐈𝐙𝐈𝐍𝐆 𝐈𝐍 𝐏𝐘𝐓𝐇𝐎𝐍, 𝐋𝐋𝐌𝐒, 𝐑𝐀𝐆, 𝐀𝐆𝐄𝐍𝐓𝐈𝐂 𝐀𝐈, 𝐀𝐍𝐃 𝐌𝐔𝐋𝐓𝐈-𝐓𝐄𝐍𝐀𝐍𝐓 𝐒𝐀𝐀𝐒.

I build production-ready AI-powered backend systems and scalable SaaS platforms that combine Python, LLMs, RAG, AI agents, automation, APIs, and secure multi-tenant architectures.

My focus is on turning complex business requirements into reliable AI products from intelligent assistants and knowledge systems to CRM automation, autonomous agents, enterprise workflows, and scalable SaaS platforms.

𝐂𝐎𝐑𝐄 𝐅𝐎𝐂𝐔𝐒:
AI Agents • LLMs • RAG • Python • FastAPI • Multi-Tenant SaaS • CRM • AI Automation • PostgreSQL • Redis • Vector Databases • AWS

𝐖𝐇𝐀𝐓 𝐈 𝐂𝐀𝐍 𝐇𝐄𝐋𝐏 𝐘𝐎𝐔 𝐁𝐔𝐈𝐋𝐃?

▸ 𝐀𝐈 𝐀𝐆𝐄𝐍𝐓𝐒 & 𝐀𝐆𝐄𝐍𝐓𝐈𝐂 𝐀𝐈
✓ Production-grade AI agents for real business workflows.
✓ LangGraph, LangChain, CrewAI, AutoGen, and custom orchestration.
✓ Tool calling, function calling, memory, planning, routing, and workflows.
✓ AI agents connected to APIs, CRMs, databases, and business systems.
✓ Human-in-the-loop and approval-based automation.
✓ Multi-agent systems for sales, support, research, and operations.

▸ 𝐋𝐋𝐌 / 𝐆𝐄𝐍𝐄𝐑𝐀𝐓𝐈𝐕𝐄 𝐀𝐈
✓ OpenAI, Anthropic Claude, Gemini, and open-source LLMs.
✓ LLM application architecture and model integration.
✓ Prompt engineering and structured outputs.
✓ Context management, memory, and conversational AI.
✓ Model selection, cost optimization, latency optimization, and reliability.
✓ Ollama and vLLM for self-hosted AI solutions.

▸ 𝐑𝐀𝐆 & 𝐊𝐍𝐎𝐖𝐋𝐄𝐃𝐆𝐄 𝐒𝐘𝐒𝐓𝐄𝐌𝐒
✓ Production-ready RAG pipelines for private and enterprise data.
✓ Document ingestion, chunking, embeddings, indexing, and retrieval.
✓ Semantic search, hybrid search, metadata filtering, and reranking.
✓ Pinecone, Qdrant, Weaviate, pgvector, and MongoDB Atlas Vector Search.
✓ Elasticsearch and AWS OpenSearch.
✓ AI knowledge bases for internal teams, customers, and enterprise applications.
✓ Retrieval optimization, evaluation, and hallucination reduction.

▸ 𝐌𝐔𝐋𝐓𝐈-𝐓𝐄𝐍𝐀𝐍𝐓 𝐒𝐀𝐀𝐒
✓ Scalable SaaS platforms supporting multiple organizations.
✓ Secure tenant isolation and organization-level data management. ✓ RBAC, permissions, authentication, and user management. ✓ Multi-tenant PostgreSQL architecture. ✓ Subscription and usage-based SaaS models. ✓ Tenant-specific AI assistants, knowledge bases, workflows, and configurations. ✓ Production-ready APIs and backend services.