Ember's AI Research Update: Generative Reporting & Data Ingestion

Here are two powerful, practical outcomes that arose from the recent AI research week involving our whole Innovation Team.

1. Data ingestion without the headache.

Most organisations shift data to generate management or investor/funder reports. One of the most common pain points is inconsistent formats and unstructured data. We explored how to create a repeatable, standardised method for handling messy inputs, regardless of format, so organisations can confidently get information into their systems without manual clean-up or rework. The output: accurate data for dashboarding and decision making.

2. AI generative reporting you can trust.

AI-powered reporting is exciting because you can pull any insight as easily as typing a prompt into ChatGPT. But accuracy is the elephant in the room and, if you use data to make decisions, confidence in the output is non-negotiable.

Our focus was on developing AI methodology that ensures information is correctly pulled from databases and validated before generating customised reports. The goal? Flexible reporting tailored to your needs without sacrificing reliability.

At its core, this research wasn’t just about building features. It was about tackling one of AI’s biggest challenges: creating structured processes for both input and output so people feel confident using it.

If your team works with data entry, reporting, or decision-making systems, we recommend you consider the power of AI generative reporting.