tela

Introducing Munari: data and operator quality scoring for robotics. Robotics teams need training data, but collection operations often lack a consistent measure of the quality of their demonstrations. Thousands of paid operator hours, with limited feedback on how to make the next hour better. We’re changing that with operator and episode quality scoring. Munari lets you: ➤ Evaluate every human demonstration against your definition of good ➤ Turn those scores into actionable feedback that improves how operators collect data ➤ Measure progress across sessions and track quality fluctuations over time This creates a feedback loop that compounds: collect, score, coach, and measure what improves. Operators learn from each session, teams refine their collection process, and the same human hours produce more usable training data. This measurement layer is the first step toward training models for reliable deployment. Making sure data teams understand what good looks like and how to consistently produce it. Our longer-term vision is to help teams benchmark and collect the right data for a specific job, environment, and robot. Knowing what you want to deploy can guide what you collect and how you evaluate it. Better data collection. Better robots. We’re already live with early partners and now opening a few more spots for pilot customers. If you’re collecting data or deploying robots, we’d love to chat!