Key Takeaways
- Caitlyn was developed specifically for research-intensive sectors where accuracy and traceability are critical.
- Agricultural organisations hold extensive research assets that are often difficult to access or apply in practice.
- The platform operates within a customer’s own cloud environment to address data sovereignty and governance.
- Early agricultural deployments show increased engagement with research and faster access to verified answers.
- Research institutions are increasingly viewing AI as long-term infrastructure rather than experimentation.
The Gap Between Research Production & Practical Use
Agriculture is among the most research-intensive sectors globally, supported by decades of trials, reports, and technical documentation. However, much of this knowledge remains under-utilised, often stored in formats that are difficult to search, interpret, or apply in time-sensitive decision-making contexts.
Josh Smith, CRO of Caitlyn, described this challenge as the starting point for the company.
“Huge investment in research, but very little of it reaching the people who need it in a usable form,” Smith said.
