Build with AI without the hype

It depends on your use case, latency budget, and data policies. We benchmark models against your real prompts and documents during discovery, then recommend a primary model plus a fallback. Most products ship with one hosted API and the option to swap models without rewriting your app.

All LLMs can hallucinate we design for it. RAG with citations, confidence thresholds, guardrails, human handoff, and eval suites in production reduce bad answers. We measure accuracy on your data before launch, not after.

API spend varies with traffic, model choice, and context size. We estimate monthly cost ranges in your proposal and implement caching, routing, and smaller models where it makes sense. You own the API keys and see usage in your provider dashboard.

Your data stays yours. We use enterprise API terms where available, keep embeddings in your vector store, and can deploy on VPC or self-hosted stacks when required. We never use client data to train public models.

Most teams start with a hosted API plus RAG it's faster and cheaper. Fine-tuning or custom models make sense when you need consistent tone, domain jargon, or strict offline deployment. We'll tell you honestly if you're not there yet.