AI/ML

We integrate AI where it solves a real problem, not where it makes a good slide. Chat interfaces that understand context, recommendation engines that surface relevant products, image generation for e-commerce, and document parsing that replaces hours of manual work.

For most use cases, API-based models (OpenAI, Anthropic) are the right choice. Fast to integrate, continuously improving, and cost-effective at moderate scale. We build the prompt engineering, context management, and output validation that turn a raw model call into a reliable feature.

RAG (retrieval-augmented generation) lets us ground AI responses in your data. Product catalogs, knowledge bases, support documentation -- we index your content with vector embeddings and retrieve relevant context before generating a response. The result is answers that are accurate and specific to your business.

For custom use cases, we fine-tune open-source models or train specialized models. Image generation for product photography, classification models for content moderation, extraction models for document processing. We evaluate accuracy, latency, and cost before recommending an approach.

Every AI feature ships with guardrails: cost controls, rate limiting, content filtering, fallback behavior when the model is unavailable, and monitoring that tracks quality over time. AI is probabilistic -- our job is to make it reliably useful.