R&D organisations face several systemic problems around data capture and access to their knowledge and learning. These include insufficient record keeping and record maintenance. Loss of implicit know-how that is only stored in people’s heads. Incomplete memory of what happened when something was tried 5-10 years ago. Data Systems that can lock in a recipe, but not the details of what didn’t work or why the final version was chosen, and are seen as dull regulatory admin. Taken together, the risk of wasting resources on un-necessary re-discovery is high.

Building a bespoke AI tool, based on the organisation’s specific knowledge has the potential to tackle these problems. Knowledge can be effectively captured, and made available in a way that ensures every team has the collective wisdom of the organisation behind them. Scientists and developers can spend more of their time focussed on decision making and moving forward.

BUT this will only work if the model is trained with the correct data and teams are trained to both train the model and to use it to support their discovery and innovation processes.

Canopy R&D is here to help design the AI enabled R&D departments of the future.

The process starts by assessing your current AI readiness.