Did Wavesteam build the AI assistant on its homepage?

Wavesteam develops and maintains the website assistant's user experience, message integration, knowledge content, and business workflow. We select underlying language-model services according to measured quality, cost, latency, and data requirements. Calling a third-party foundation model is not presented as having developed that foundation model ourselves.

For an enterprise AI application, the most valuable custom work is rarely the chat bubble. It is the approved sources and versioning, retrieval and citations, user permissions, tool calls, refusal and human handoff, operating logs and evaluation, cost controls, and data boundaries.

When applying case experience to a new project, also compare Which industries has Wavesteam worked in? and Does Wavesteam have experience with a similar industry or level of complexity?; the linked guidance adds context that should be considered in the same decision.

We can demonstrate how the assistant cites content, responds when evidence is absent, enters a business workflow, and is retested after a knowledge change. That demonstration is evidence of application engineering, not proof that the same design will work for every client's sources and users.

To evaluate a similar application, the client can provide a small authorized and de-identified source set, representative questions, and an empowered answer owner. Wavesteam designs a bounded evaluation and reports evidence-supported correctness, refusal, human-review burden, latency, and full cost per task. Formal development follows only when those results justify it.