Openlayer Raises $4.8M To Enhance AI Debugging Workspace


Machine learning validation and testing platform Openlayer has closed a $4.8 million seed round, led by Quiet Capital, to expand its workforce and enhance the platform’s functionality so it is capable of handling additional machine learning (ML) tasks. Already, startups to Fortune 500 companies are using Openlayer to test and validate their machine learning models, uncover unexpected mistakes, and diagnose why and when they’re happening.

The seed round will enable the Openlayer team to create more sophisticated guardrails for customers to test their models against as they iterate. The platform will also allow for edge-case detection using synthetic data to generate test cases they might not have considered. Importantly, customers will benefit from faster, more organized development velocity.

Openlayer’s founding team is composed of former Apple ML engineers who have firsthand experience building AI at scale. Other members of the company include an ex-Amazon engineer and a Harvard Design Engineering school graduate.

Openlayer helps teams systematically improve their models and datasets by:

  • Verifying the integrity of training and validation datasets
  • Surfacing meaningful discrepancies between training, evaluation and production data
  • Ensuring models meet their target performance benchmarks
  • Validating models are robust to edge-cases by generating synthetic data to inject noise and conduct adversarial attacks
  • Guaranteeing fairness of model behavior across data subpopulations
  • Tracking versions of models and datasets and comparing their performance
  • Explaining model behavior by surfacing which features of the data were used to make a prediction

The funding round saw participation from Picus Capital, YCombinator, Hack VC, Liquid2 Ventures, Mantis VC and a host of angel investors including Instagram co-founder Mike Krieger, Instacart co-founder Max Mullen and many others.