AI Observability Platform Vendor WhyLabs Closes $10M Series A Funding Round 

As more enterprises integrate AI into their infrastructures and business processes, one of the difficulties that often arise is knowing how the systems are working and what changes are needed to make them more efficient and productive.

With that mission in mind, AI observability vendor WhyLabs just announced the closing of a $10 million Series A round investment to help the company expand and grow its nascent WhyLabs AI Observatory SaaS platform, its staff and its operations. The AI Observatory platform is designed to help enterprises monitor and understand what is going on within their AI systems and applications, including data health and model health.

The $10 million in new funding was co-led by Defy Partners and Andrew Ng’s AI Fund, with participation from existing investors including Madrona Venture Group and Bezos Expeditions.

Alessya Visnjic of WhyLabs

“Over the past year, the WhyLabs AI Observatory platform has been deployed at logistics, fintech, marketing, retail, and healthcare enterprises,” Alessya Visnjic, the CEO at WhyLabs, told EnterpriseAI. “In October, we opened up the enterprise platform and made it available as a self-serve SaaS. Since the SaaS launch, the number of models monitored tripled, and we added two dozen new organizations.”

The platform is designed to provide usable tools that can make it easier for enterprise developers to monitor their complex production ML models, said Visnjic.

“As enterprises deploy ML and AI models to production, they are faced with the challenge of ensuring that these models deliver desirable customer experience and realize ROI,” she said. “Observability and monitoring empowers AI practitioners to reap the benefits of AI without the spectacular failures that so often make the news.”

WhyLabs built its platform because its founders believed that existing tools are not sufficient, said Visnjic.

“Today, most of our competition is manual, homebuilt tools that ML engineers and data scientists put together to tackle day-to-day ML operations,” she said. “Nearly every ML team we talk to has a collection of Jupyter notebooks or simple reports for detecting data outages, data drifts or model performance issues.”

WhyLabs differs from its competitors, which include cloud providers like AWS and Google that offer platform-specific monitoring features for their own products, and startups like Truera and Fiddler AI, she said. The WhyLabs platform allows enterprises to monitor data and model health in a platform-agnostic way, while focusing on privacy and being massively scalable for growing business operations, she added.

The platform enables observability across a wide range of use cases such as ranking, recommendations and personalization, document understanding, image understanding, forecasting and fraud detection, according to the company.

So far, the company says it has a mix of enterprise and self-service customers including AI-first startups and Fortune 500 companies in a range of markets, including fintech, logistics, manufacturing, real estate, retail, ecommerce and healthcare.

AI Observatory is available for free use to enterprises. It can be connected to AI systems through plug-ins for Python or Java (including Apache Spark) ML systems, according to the company.

In October, AI monitoring vendor Mona Labs and cloud-based software stack observability platform vendor New Relic announced a partnership to combine their efforts to help enterprises better monitor, analyze and troubleshoot their growing production AI workloads.