I build autonomous, agentic AI systems that help businesses and high-growth startups automate complex workflows, unlock their proprietary data, and scale operations

I don't just write API wrappers or build generic, easily confused chatbots. I act as a strategic AI engineering partner to founders and business owners. Whether you need to integrate sophisticated LLMs into your SaaS product, build secure RAG pipelines to query your internal databases, or deploy voice-native Conversational AI for 24/7 customer support, I engineer solutions focused strictly on measurable business ROI.

From architecting multi-agent frameworks using the latest Model Context Protocol (MCP) to fine-tuning context windows for Claude and GPT-4, my focus is always on delivering secure, reliable, and hallucination-free AI systems that are ready for production.

AI AGENTS & WORKFLOW ORCHESTRATION Agentic Frameworks: Building autonomous, tool-calling agents using Model Context Protocol (MCP), LangGraph, and CrewAI.

Process Automation: Seamlessly connecting AI to your business systems (CRMs, ERPs, databases) using n8n, Make, and custom API integrations.

Multi-Step Reasoning: Designing AI workflows that can plan, execute, and evaluate complex multi-stage tasks without human intervention.

RAG & PROPRIETARY DATA (LLMs) Models: Deep expertise in Anthropic Claude 3.5 (Sonnet/Opus), OpenAI GPT-4o, and open-weight models (Llama 3, Mistral).

Retrieval-Augmented Generation (RAG): Building secure pipelines that allow AI to perfectly "read" and cite your company's PDFs, Notion docs, and databases.

Vector Infrastructure: Pinecone, Weaviate, ChromaDB, and advanced chunking/embedding strategies for highly accurate semantic search.

CONVERSATIONAL & VOICE AI Voice Agents: Deploying sub-second latency, human-sounding voice bots for inbound/outbound calls using Vapi, Bland AI, and ElevenLabs.

Customer Support: Building dynamic, memory-retaining conversational interfaces that actually resolve customer tickets, rather than just deflecting them.

Multimodal AI: Processing and generating insights from images, audio, and text simultaneously.

PRODUCTION-GRADE DEPLOYMENT Cloud & Edge: Deploying highly available AI backends on AWS and GCP.

AI Observability: Implementing logging and tracing (LangSmith) to monitor token usage, track agent behavior, and continuously optimize prompt costs.