Custom AI Application Development
Secure, scalable, and tailored Generative AI solutions that give your business
a genuine competitive advantage over off-the-shelf tools.
The Problem
Off-the-Shelf AI Is Not Enough
Tools like ChatGPT and Claude are powerful, but they are generic. They cannot access your proprietary databases, understand your internal business logic, or comply with your enterprise data privacy requirements. If you want AI that actually moves the needle for your business, you need a custom-built solution architected specifically for your infrastructure.
What I Build
My AI Development Capabilities
🔍 Retrieval-Augmented Generation (RAG)
I build custom RAG pipelines that connect your AI directly to your private company documents, wikis, databases, and knowledge bases. Your AI reads and understands your proprietary data in real-time — completely eliminating hallucinations and delivering accurate, source-cited answers every time.
🤖 Autonomous AI Agents
Move beyond simple chatbots. I architect multi-agent systems using LangChain and LlamaIndex that can autonomously research data, execute API calls, process transactions, generate reports, and make complex logical decisions — running entire workflows without human intervention.
🔒 Local & Private LLM Deployments
Bound by strict data compliance regulations like GDPR, HIPAA, or SOC 2? You cannot send sensitive customer data to third-party API servers. I specialize in deploying ultra-secure, open-source models like Llama 3 and Mistral directly onto your own private cloud infrastructure on AWS, GCP, or Azure.
⚡ Vector Database Architecture
Scalable AI requires a completely new data paradigm. I design high-performance vector databases using Pinecone, Weaviate, pgvector, or Milvus to ensure your custom AI application retrieves relevant context from billions of embeddings with sub-millisecond latency.
Tech Stack
The AI Frameworks I Use
Orchestration
LangChain
LlamaIndex
CrewAI
LLMs
OpenAI GPT-4o
Anthropic Claude 3.5
Meta Llama 3
Mistral
Vector DBs
Pinecone
Weaviate
pgvector
Milvus
Infrastructure
AWS / GCP
Docker
Vercel
Next.js / React
Ready to Build Your Custom AI Solution?
Tell me about your data, your infrastructure, and your goals.
I will deliver a free AI architecture roadmap within 24 hours.
FAQ
AI Development Questions
How long does it take to build a custom AI application?
A production-ready MVP typically takes 6-12 weeks depending on complexity. A simple RAG chatbot connected to your documents can be deployed in as little as 3-4 weeks. Enterprise multi-agent systems with complex integrations may take 3-6 months.
Can you build AI that works with my existing software?
Absolutely. I specialize in integrating AI into existing enterprise infrastructure — whether that means connecting to your legacy ERP system, your CRM APIs, your internal databases, or your cloud storage. The AI layer is designed to complement and enhance what you already have, not replace it.
Is my data safe with a custom AI solution?
Data security is my top priority. For clients with strict compliance requirements, I deploy fully private, on-premise or private-cloud LLMs (Llama 3, Mistral) so your sensitive data never leaves your infrastructure. All architectures include encryption at rest, in transit, and role-based access controls.