What AI unlocks: de-risking innovation
AI enables us to move rapidly from concept to web tool, without the need for extensive coding. We define the data sources and methodologies, and instruct AI to visualise this in an interactive data tool as per our criteria. Following data validation, we can then publish the prototype to invite user feedback and iterate on the design in a more practical and hands-on way – or fail fast and move to the next concept.
This co-creation process can rapidly lead us to a working prototype, and we can then secure funding and partnerships to turn the ideas that are most useful for policymakers and investors into fully-fledged Ember data tools.
Turning prototypes into Ember-approved data tools
Ember has a reputation for high-quality and useful data products that are trusted by policymakers and investors for high-impact decision-making.
To transition from an AI-assisted prototype to an Ember-approved tool, every project will eventually go through our rigorous production process:
User-informed design – ensuring tools are useful and easy to use for the intended audience.
Data architecture and validation – integrating datasets and methodologies into our core databases, with rigorous data validation and ongoing maintenance and data updates.
High-quality data tool production – Ember’s front-end developer designs and codes the user interface and database integration, informed by our data visualisation experts, data architects and policy specialists.
Targeted audience outreach and training – ensuring data tools reach target audiences – via direct outreach, digital promotion and top-tier media coverage – and that users are equipped to generate real insight from the tools.
What we’re finding is that the key ingredients of an Ember data tool haven’t changed with AI, but the route to delivery can be improved and accelerated with AI assistance.
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