Mira Studio

Before Mira, generating insights in Meltwater required deep platform expertise. Users had to construct precise Boolean queries, configure dashboards across multiple surfaces, and manually interpret results. For new users, this created a steep learning curve that slowed onboarding and limited adoption. Even experienced analysts were spending more time setting up analysis than actually analysing. The platform was powerful, but not intuitive.

We began by reframing the experience from a tool-driven model to an intent-driven one. Instead of asking users to configure searches or dashboards, we centred the interaction around a simple question: What do you want to know? This shift became the foundation for a conversational interface generating insights through natural language. One of the critical focuses was trust — AI-generated insights can feel like a black box if not designed carefully. We ensured outputs were structured, contextual, and easy to interpret, while still allowing users to refine, customise, and iterate on prompts.

Mira Studio became the primary workspace for generating insights — users could ask questions about their brand, competitors, or industry trends and instantly receive structured reports, eliminating the need to manually build dashboards. The Prompt Library allowed users to save, organise, and reuse prompts for common analyses, turning individual knowledge into scalable team workflows. The Mira Companion embedded contextual prompts and insights directly into the platform based on what users were viewing, enabling action without leaving the current workflow.