“When enterprises deploy AI, there’s no room for error,” says Openlayer CEO

“The rate of AI adoption is accelerating rapidly, with teams integrating AI into more mission-critical aspects of their business,” said Gabriel Bayomi, CEO and co-founder of Openlayer.

AI system failures can have significant financial consequences, exemplified by Zillow’s Zestimate model losing over $500 million due to its inability to adapt to pandemic housing market shifts. These costly errors frequently arise from insufficient validation and governance, resulting in issues like hallucinations, data leakage, and incorrect forecasts in sectors including finance, telecom, and e-commerce.

Enhancing AI Reliability

A unified platform addresses the complexities of the AI model lifecycle, from experimentation to production deployment. Founded by Gabriel Bayomi, Rishab Ramanathan, and Vikas Nair  of Apple, Amazon, and Harvard’s Design Engineering School, the platform supports both traditional machine learning and generative AI. It enables teams to manage critical aspects like data quality, model evaluation, and governance, ensuring reliable AI performance in real-world scenarios.

Openlayer just announced that it successfully raised $14.5 million in a Series A funding round led by Race Capital, with participation from NXTP Ventures, Mindset Ventures, Y Combinator, Quiet Capital, Wayra, KPN Ventures, and Mento VC. This funding will enable Openlayer to expand its enterprise-grade features and scale its go-to-market plans across key industries and global markets.

The company incorporates AI across its platform to increase the reliability, performance, and compliance of AI systems throughout their life cycle. Utilizing AI-based tools, Openlayer provides monitoring, evaluation, and governance solutions for both standard machine learning (ML) models as well as sophisticated generative AI applications, such as large language models (LLMs).

This facilitate real-time monitoring of AI systems, where teams can catch anomalies, measure quality, and react quickly to problems as they happen. Some of the features include drift detection, which captures changes in data distributions or spiky predictions, to ensure that models remain accurate and reliable even in changing conditions.

Collaborative Compliance for AI Deployment

The platform uses AI to test and validate AI models automatically. This entails execution of behavior tests correlated with business results, detection of edge cases and regressions prior to deployment, and guaranteeing that models behave as expected. Automation of these processes reduces the time and resources used in manual testing, thus speeding up the development cycle.

As Bayomi continues to state, “When enterprises deploy AI, there’s no room for error, especially in customer-facing applications. A single failure can erode trust, disrupt lives, or lead to legal and reputational fallout. That’s why robust evaluation, observability, and governance aren’t optional – they’re foundational to responsible AI deployment.”

Therefore, Openlayer distinguishes itself in critical applications demanding reliability and robust governance, all while prioritizing a developer-centric experience that encourages organic adoption throughout organizations.

Openlayer, which previously stated that several Fortune 500 companies utilize its platform, today identified Amdocs Ltd. and Telefonica as users of its AI model evaluation tools. The company plans to invest the proceeds from its latest funding round in enhancing its enterprise features and expanding its market reach in important sectors and international markets.