Exposé helped an education provider develop a scalable conversational AI framework using explAIn and Microsoft Azure.
The Problem
A leading education provider identified growing friction in how prospective students engaged with course information through their existing digital channels. The process often felt overwhelming and difficult to navigate, falling short of the expectations set by modern conversational experiences.
Their internal teams recognised that static websites and traditional FAQs were no longer effective in supporting users who make complex, high-stakes decisions, such as selecting a course. They needed a more intuitive and responsive way to guide students through this journey.
While committed to innovation, the organisation had limited experience with AI and needed a low-risk way to explore its potential. As an Azure-based environment, they also required a solution that provided transparency and control over user interactions, allowing them to track what was being asked, when, and why. Ensuring this level of oversight was essential to maintain trust, meet internal standards, and inform future decisions.
The Solution
Exposé delivered a focused five-week proof of value engagement using our explAIn accelerator, built on OpenAI models and deployed within the client’s Azure environment. The objective was to explore how a conversational assistant could help prospective students discover and select courses, while aligning with the organisation’s digital standards and tone of voice.
Using explAIn enabled faster development and reduced setup time, allowing rapid deployment of a controlled test environment. This supported iterative development, stakeholder feedback, and structured A/B testing of different conversational approaches. Real organisational data was vectorised from the client’s PostgreSQL-based content sources, enabling accurate and context-aware responses.
The assistant was designed to match the look and feel of the organisation’s existing digital experience, with a focus on clarity, relevance, and ease of use. Supporting documentation, testing frameworks, and recommendations were delivered to guide next steps and enable long-term value. The outcome was a validated and measurable foundation for broader AI adoption, aligned with the client’s Azure-first strategy.
Business Benefit
The proof of value demonstrated that Exposé’s explAIn accelerator, built on OpenAI models and deployed within the client’s Azure environment, could significantly enhance the prospective student experience. Users accessed relevant course information more efficiently, especially when unsure how to phrase queries or navigate traditional content structures.
A/B testing confirmed that different conversational strategies led to distinct engagement patterns, underscoring the need for thoughtful design and tuning. The assistant consistently met defined performance benchmarks, reducing friction and supporting confident decision-making.
Stakeholders agreed that the engagement validated the use of conversational AI in a real-world context. Delivered through explAIn, the solution improved information access, supported intuitive exploration, and aligned with the organisation’s digital strategy. All without requiring major system changes. With a scalable, well-documented foundation in place, the client is now positioned to grow its AI capability with confidence.
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