ADD AI CAPABILITIES TO YOUR APPLICATIONS
Integrate large language models into your products with proper architecture, prompt engineering, and production-grade reliability.
Why Work With Me?
- Add AI capabilities to existing applications
- Choose the right model for cost, latency, and quality
- Build robust error handling and fallback strategies
- Implement proper prompt engineering from day one
- Set up evaluation pipelines to measure quality
- Design for scale: caching, batching, rate limiting
What I Deliver
API Integration
Connect your applications to OpenAI, Anthropic, Azure OpenAI, or self-hosted models. Proper error handling, retries, and monitoring included.
Prompt Engineering
Design prompt templates that produce consistent, high-quality outputs. Structured outputs, few-shot examples, and chain-of-thought patterns.
Production Deployment
Deploy LLM-powered features with caching, rate limiting, cost monitoring, and quality evaluation. Built for reliability at scale.
Models I Work With
OpenAI GPT-4
Best overall quality, function calling
Anthropic Claude
Long context, safety, reasoning
GPT-4o Mini
Cost-effective for high volume
Llama 3
Self-hosted, data privacy
Mistral
European hosting, good performance
Azure OpenAI
Enterprise compliance, SLAs
Common Questions
Which LLM should I use for my project?
It depends on your priorities. GPT-4 for quality, Claude for long documents and reasoning, GPT-4o-mini for cost optimization, Llama/Mistral for data privacy. I help you evaluate trade-offs and choose the right model for each use case.
How do you handle API costs?
Cost optimization is built into every integration: response caching, prompt optimization, model selection by task complexity, and batching where possible. I set up monitoring so you can track spend by feature and user.
Can you help with existing LLM implementations that aren't working well?
Yes. I audit existing implementations, identify issues (usually prompt design, lack of evaluation, or architectural problems), and fix them. Often small changes to prompts and architecture lead to significant quality improvements.
Do you work with open-source models?
Yes. For clients with data privacy requirements or high-volume use cases, I implement solutions using Llama, Mistral, or other open-source models. Self-hosted or via providers like Together, Groq, or Fireworks.