We in-housed our data labelling

At Enhanced Radar, we’ve developed Yeager, a SOTA model that understands air traffic control audio, and we continue to develop other AI models for aviation applications. Due to the industry-specific technical complexity of our data, we could not possibly outsource this labelling effort to a third party and still meet our quality standards, forcing us to label our data in-house. Looking back, our decision to control our own labelling was vindicated at every step. The iterative process of building our labelling engine was the result of 1:1 relationships with our hundreds of (domain expert) reviewers, thousands of emails, and dozens of internal product updates, that now allow us to label a huge volume of messy data at a high degree of standardization and near-perfect accuracy — all with minimal intervention. Incentive Alignment Obvious but necessary: to incentivize productive work, we tie compensation to the number of characters transcribed, and assess financial penalties for failed te ... Read full article.