AI Development Services

Looking for an AI developer? I build production-ready AI solutions with LangChain, RAG systems, and multi-agent architectures. 7+ years of full-stack experience, 15+ projects delivered.

What I Build

From simple AI integrations to complex multi-agent systems — I deliver solutions that work in production.

LangChain Development

Build sophisticated AI workflows and chains using LangChain. From simple chatbots to complex multi-step reasoning systems with memory, tools, and external integrations.

  • Custom chain architectures
  • Tool and function calling
  • Conversation memory systems
  • Streaming responses

RAG Systems

Implement Retrieval Augmented Generation systems that combine your proprietary data with LLM capabilities. Perfect for knowledge bases, documentation assistants, and enterprise search.

  • Vector database integration
  • Semantic search optimization
  • Document chunking strategies
  • Hybrid search (semantic + keyword)

Multi-Agent Systems

Design and build systems where multiple AI agents collaborate to solve complex problems. Navigator, Planner, Executor, Validator — each agent specialized for its role.

  • Agent orchestration
  • Inter-agent communication
  • Self-validation loops
  • Automatic fallback patterns

LLM Integrations

Integrate multiple LLM providers (OpenAI, Anthropic, Google, local models) with unified interfaces and automatic failover for production reliability.

  • OpenAI GPT-4 / GPT-4o
  • Anthropic Claude
  • Google Gemini
  • Local models (Ollama, LMStudio)

Technologies I Use

Modern AI stack for building scalable, production-ready solutions

LangChainLangGraphOpenAI APIAnthropic APIPineconeWeaviateChromaDBPythonTypeScriptFastAPINestJSPostgreSQL

AI Projects

MealPlan AI Agent

AI-Powered Meal Planning

AI meal planning platform powered by LangGraph StateGraph for meal generation, RAG pipeline with Qdrant for semantic recipe retrieval, and Langfuse for full LLM observability. Structured output validation ensures dietary constraints are enforced across non-deterministic LLM outputs.

LangGraph
StateGraph with generation, validation, diversity enforcement nodes
RAG Pipeline
Qdrant vector DB + USDA nutritional validation
SSE Streaming
Real-time Python → NestJS → Next.js streaming
Langfuse
Token/cost tracking, trace visualization, prompt versioning
View Project

GovChime Analytics Platform

Government Contracts Intelligence

Architected AI pipeline for government contract data: automated data sanitization, contract opportunity matching, and description generation via LLM APIs. Structured output validation ensures consistent data quality across 70M+ rows. Full agentic development workflow with Claude Code, custom agent skills, and MCP integrations.

100-300%
Query time reduction via ClickHouse OLAP + materialized views
70M+ Rows
Production dataset with real-time analytics
7 Packages
Monorepo with 3 SmartSync microservices + API + frontends
24+ Workflows
CI/CD pipeline: unit → integration → E2E → deploy
View Project

Formea AI Form Automation

Multi-Agent Chrome Extension for Intelligent Form Filling

Architected multi-agent system with 3 specialized agents (Planner, Navigator, Validator) orchestrated by an Executor with self-validation loops. LangChain integration supporting 8 LLM providers with automatic structured output fallback via Zod schemas. Built VBON Form Explorer agent for autonomous government form reverse-engineering using stable IDs and deterministic DOM diffing.

3 Agents
Planner, Navigator, Validator with self-validation loops
8 Providers
LLM provider support with automatic fallback
10K+ HTML
Government form handling via VBON Form Explorer
Solo Dev
Full-stack AI Chrome Extension built from scratch
View Project

AI Development FAQ

What types of AI projects do you work on?

I specialize in production AI systems: chatbots with memory, RAG-powered knowledge bases, AI agents that can browse the web and fill forms, multi-agent systems for complex workflows, and LLM integrations into existing applications.

How long does it take to build an AI solution?

A simple chatbot with RAG can be production-ready in 2-4 weeks. More complex multi-agent systems typically take 6-12 weeks. I always start with a discovery phase to scope the project accurately.

Can you integrate AI into my existing application?

Yes, I regularly integrate AI capabilities into existing systems. Whether it's adding a conversational interface, implementing semantic search, or building an AI-powered feature — I can work with your existing tech stack.

What makes your AI solutions production-ready?

I focus on reliability: automatic fallbacks between LLM providers, comprehensive error handling, rate limiting, response validation, and proper logging. My solutions are built for real users, not just demos.

Ready to Build Your AI Solution?

Let's discuss how AI can transform your business. Free discovery call, no commitment.

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