CI is bought twice: first the data subscriptions, then the manual work of synthesizing them. Two expensive purchases that still leave a team working from the same incomplete picture, where records are stale, signals late, and a shift in the landscape means doing much of the work again. That is why CI has always had to pick two of faster, cheaper and better. This session shows what changes when one system holds both layers: a data layer that is broader and fresher, and an agentic layer that turns an objective into a complete, cited analysis. Faster, cheaper, better, all three, with the team's time going to judgment rather than assembly. Live demos of Ferma's agentic AI suite, including a competitive landscape built on stage.
Key takeaways
- Why buying data and buying synthesis still leaves a team working from an incomplete picture
- What changes when the data layer and the agentic layer become one system
- Why a refresh stops meaning doing much of the work again from scratch
- A competitive landscape, built live on stage, on a disease the room picks
