Research
An agent that can sell is the direct path to a world of abundance.
Teaching frontier models to sell, optimise sales, and drive revenue strategy effectively requires high quality datasets and realistic training tasks that are exceptionally difficult to source, prepare and structure into verifiable outputs for model improvement.
Research approach
Our research ambition is to give model builders at the frontier and in the enterprise the datasets, realistic tasks and training environments to build agents that can sell, and turn previously unverifiable tasks into graded, verifiable results.
Hypothesis
Identify a capability gap and define what improvement would look like.
Structure
Define the task, the training approach and how success will be judged.
Source & create
Source relevant data and shape it into realistic training tasks.
Evaluate
Measure model improvement, benchmark progress and iterate.
Productionise
Scale the datasets and tasks that demonstrate improvement.