Today, Gretel.ai closed a $50 million Series B funding round, led by Anthos Capital, along with participation from Section 32, and existing investors Greylock and Moonshots Capital, bringing the total funding raised to date to $65.5 million. This new funding helps accelerate Gretel’s pioneering work on its Privacy Engineering as a Service platform and suite of tools for developers. The funding will fuel Gretel’s continued innovation with high-quality synthetic data, and expansion into new use cases linked to data privacy.
To survive and scale, businesses must put in place robust data privacy measures, and the cost for doing so has been prohibitively expensive. Big Tech can afford to hire specialized privacy engineers to anonymize critical data assets directly, while developers everywhere else wait weeks to months for compliance approvals to access similar data – until now. Gretel’s tools enable all developers and data practitioners to implement intelligent, high-quality data privacy measures, so they can quickly and safely innovate with data – at a fraction of the time, cost, and risk to their users’ privacy and their brand.
“This significant Series B investment is a direct reflection of Gretel’s ambitious vision, swift growth, and strength of position in the AI industry as the standard-bearer of tools that enable privacy by design,” said Emily White, President of Anthos Capital. “Gretel’s ease of use, the extendability of its services, and the superior accuracy and quality of its synthetic data are much-needed solutions to simplify the exceedingly complex legal and technical barriers companies face due to data privacy concerns.”
Gretel’s platform enables developers to synthesize, transform, and classify data with an easy-to-use suite of tools and APIs that aim to eliminate data privacy issues through safe data sharing. By applying advanced AI and ML techniques, Gretel generates the most accurate, private, and high-quality synthetic data of any product in its class, and with significant time savings for engineers. With the new funding, Gretel will continue to advance the AI capabilities of its platform to support customer use cases in life sciences, financial, gaming, and technology industries. For example, health-tech companies are looking to enable information sharing and monetize data while protecting the privacy of patients and minimizing biases that could be inadvertently learned by algorithms trained on shared datasets.
“Gretel gives data teams working in any framework or language the tools they need to build privacy by design into their existing workflows and data pipelines, greatly simplifying this process,” said Sridhar Ramaswamy, partner at Greylock. “Time and time again I hear from software engineers and data scientists about the value Gretel offers. Its developer-first, tech-agnostic approach to solving privacy issues is incredibly valuable to every business sector.”
“The drive behind the last two decades of investment in cloud-native and developer tooling has been to power high-velocity development in ML/AI, IoT, and all applications,” said Ali Golshan, Co-founder and CEO of Gretel.ai, “which requires access to enormous volumes of data that is bound by ethics, privacy regulations, and public trust. At Gretel, we are building tools that enable privacy by design, which in turn provides fast and easy access to data that fuels innovation with privacy by building it into the fabric of applications. That’s Gretel’s mission.”
Gretel has an open Beta program that developers can sign up for, start building for free, and provide feedback to the team directly. Gretel is also looking to grow its team and recruiting for a number of roles. Details can be found on their careers page.
Gretel is a privacy engineering toolkit featuring simple APIs and an open-source AI-based core, built for developers. Companies and developers use Gretel’s easy-to-integrate APIs to classify and label, transform and anonymize, or create synthetic data to quickly and safely build and collaborate with data. Gretel customers use our services either as a SaaS offering, or run our CLI and APIs in their own environments.