Interactive Gen AI eConcierge Avatar
Venues needed a conversational layer that could answer visitor questions, check availability, recommend events, and take simple actions—without overloading frontline staff. This case study covers an AI-powered eConcierge avatar where prompt design directly shaped accuracy, tone, and which real-time behaviours the assistant could safely perform at scale.
Role
I worked as a Prompt Engineer on an AI-powered eConcierge avatar, designing and optimizing prompts to enable accurate, context-aware, and conversational interactions. I collaborated with cross-functional teams to translate user needs and service requirements into structured prompt strategies that guide the AI’s responses and actions effectively.
Approach
I adopted an iterative, user-centered approach to design and refine prompt frameworks that handle high-volume visitor queries. This included defining intent recognition patterns, crafting persona-driven responses, and structuring prompts to support tool-calling for real-time actions such as checking availability and recommending events. I focused on improving response accuracy, consistency, and conversational flow, while continuously testing and tuning prompts based on edge cases and user interactions to ensure reliability at scale.
Outcome
The eConcierge shifted repetitive work off frontline teams, lifted answer quality and visitor satisfaction, and proved the assistant could scale with traffic while leaving room for multilingual expansion.
35–50%
Less frontline workload
By automating repetitive visitor queries
Stronger
Accuracy & satisfaction
More consistent responses and higher visitor satisfaction
Scale
High-volume ready
Handles heavy query loads with a path to multilingual expansion
- Prompt engineering
- Conversation design
- Intent recognition
- Tool-calling design
- Iterative testing
- Persona-driven prompts
- Cross-functional collaboration
- Documentation