SAN FRANCISCO--(BUSINESS WIRE)--Openlayer, the creator of the world’s most comprehensive platform for testing AI, today announced that it has closed a $4.8 million seed round. The funds will be used 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.
“As ML becomes more popular and more accessible, it’s critical we put the right guardrails in place for models entering the real world. Testing should be a vital part of building ML models from the start, as opposed to as an afterthought,” said Rishab Ramanathan, co-founder of Openlayer. “Such test-driven development is the only way to meaningfully align models with human interests. Doing this in a repeatable way requires a platform that makes battle-tested models a reality.”
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.
“Over the course of our time working across 15 different teams at Apple, we faced firsthand the same problem over and over: there is no standardized way to test and collaborate on machine learning models,” said Vikas Nair, co-founder of Openlayer. “Because of this, errors are often not caught until after shipping, which can result in potentially disastrous outcomes.”
While numerous software testing platforms exist, those platforms are designed for deterministic systems in which a given input will produce an expected output. Since ML models are probabilistic, there has been no way to test them reliably until now.
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
Investors and planned expansion
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.
“Over the long term, we envision a future in which many of the processes for detecting and fixing errors can be automated with Openlayer,” said Gabriel Bayomi Tinoco Kalejaiye, co-founder of Openlayer. “Our vision is to be the go-to hub for any ML team shipping models. To achieve this requires building a development pipeline that delivers powerful insights about your models and data every step of the way, pre- and post-deployment.”
Quiet Capital is the lead investor with participation from:
- Picus Capital
- Hack VC
- Liquid2 Ventures
- Mantis VC
- Jonathan Swanson, founder of Thumbtack and an investment consultant for Greystone Consulting
- Mike Krieger, co-founder, Instagram
- Max Mullen, co-founder, Instacart
- Guillermo Rauch, CEO and founder of Vercel
- Gokul Rajaram, member of the board of directors, Coinbase, Pinterest, and The Trade Desk
- Immad Akhund, co-founder CEO, Mercury
- Oliver Cameron, VP, Product, Cruise
- Yuri Sagalov, managing partner, Wayfinder Ventures
- Rodrigo Schmidt, head of engineering, NPE at Meta
- John Kim, CEO, SendBird
“AI adoption is on the rise, and we are seeing the importance of data-centric ML as algorithms become commoditized,” said Astasia Myers, enterprise partner at Quiet Capital. “The Openlayer founders worked on ML at Apple and saw firsthand the benefit of having data-centric ML solutions that supported test-driven development and data quality analysis. The founders took their unique insight and applied it to building Openlayer that solves this need for all businesses. They are tackling a critical problem around ML data intelligence which we expect will continue to boom with AI’s increased ubiquity.”
Openlayer is a machine learning validation and testing platform that enables teams to efficiently detect, diagnose, and correct model failures. Openlayer sets itself apart by simplifying the process of identifying errors before models enter production and then monitoring performance over time, effectively bringing observability to every stage of development. In May 2022, CB Insights named Openlayer to its annual AI 100 ranking.