Give your agent the precise context for every turn.

Most teams build agents bottom-up: a growing list of intents that overlap, conflict, and confuse the model. We take a different approach. Emily’s journey issues are mapped MECE across your user journey — so every conversation routes to the right issue, faster and with less ambiguity.

A domain-specific language that lets Emily enforce critical SOP steps deterministically — while still holding a natural, human-like conversation. You get the reliability of a workflow engine and the flexibility of an LLM, without choosing between them.

Variables are Emily’s working memory — the business signals she tracks and reasons over in every conversation. Translate raw backend data into meaningful variables, design and test them offline with AI, then execute as code at runtime.

The best human agents don’t just answer questions — they clarify intent, remind customers of next steps, collect missing details, verify identity, and exercise judgment. Emily does the same, and executes account-related operations with the precision of a system call.