Turn Your Data Into a Competitive Advantage

We work on a wide range of AI initiatives: LLM-powered features, RAG-based knowledge systems, semantic search, predictive analytics, recommendation engines, and custom AI agents. If it involves making a product smarter with data or language models, we're interested.

Yes — we're model-agnostic. We've deployed production systems using OpenAI GPT-4o, Anthropic Claude, Mistral, Llama, and fine-tuned domain-specific models. We recommend the best fit for your accuracy, cost, and latency requirements.

We use retrieval-augmented generation (RAG) architectures to ground responses in your verified data, combined with output validation layers, confidence thresholds, and human-in-the-loop review flows for critical decisions.

Absolutely. We frequently add AI capabilities to existing applications via API integrations, embedded widgets, and microservice architectures. Our AI Interface Layer makes it easy to add, swap, or upgrade AI features without touching your core product.

A focused AI feature (e.g., semantic search, a Q&A assistant, a classification pipeline) typically takes 4–10 weeks from kick-off to production deployment. More complex multi-model systems or data infrastructure projects run 3–6 months.