The company has amassed a total funding of US$19.3 million.
DynamoFL, Inc., an enterprise AI platform specializing in privacy-centric generative AI solutions, has successfully concluded a Series A funding round, securing US$15.1 million. This boost comes amid increasing demand for AI technologies that seamlessly integrate both privacy and compliance.
With a previous seed round of US$4.2 million, DynamoFL’s total funding now stands at US$19.3 million. The core technology of this San Francisco-based startup enables customers to securely train large language models (LLMs) on sensitive internal data. It is already in active use by Fortune 500 companies across various sectors, including finance, electronics, insurance and automotive.
This funding round was jointly spearheaded by Canapi Ventures and Nexus Venture Partners and was further bolstered by investors such as Formus Capital and Soma Capital. A roster of angel investors, including names such as Vojtech Jina, privacy-preserving machine learning (ML) lead from Apple, Tolga Erbay, Dropbox’s Head of Governance, Risk and Compliance, as well as Charu Jangid, product leader at Snowflake, also pitched in.
Behind DynamoFL’s vision are two MIT Ph.D. holders who’ve extensively researched privacy-centric AI and ML. The team’s academic prowess, associated with institutions like MIT, Harvard and Cal-Berkeley, is complemented by their field experience with tech behemoths like Apple, Meta, Microsoft and Palantir. The company’s suite of tools and solutions emphasizes privacy and compliance, a perspective Vaikkunth Mugunthan, DynamoFL’s CEO, believes is crucial for AI’s successful integration into the enterprise environment.
Addressing the urgent need for secure AI solutions
With AI becoming ever more integrated into business operations, there are increased risks associated with data security and privacy. LLMs, in particular, can inadvertently memorize and reveal sensitive information, posing significant security threats.
Regulatory environments across the globe, such as the European Union’s General Data Protection Regulation (GDPR), the upcoming EU AI act and similar initiatives in China, India and the U.S., necessitate that businesses remain aware of these risks and implement safeguards. However, currently, businesses lack the means to detect and address the risk of data leaks.
DynamoFL seeks to bridge this gap. As government bodies like the Federal Trade Commission (FTC) delve into concerns about LLM providers’ data security, DynamoFL’s machine learning privacy research team recently spotlighted vulnerabilities in the GPT-3 model, which could be manipulated to leak sensitive data about top executives, Fortune 500 companies and private contract values. To combat this, DynamoFL offers specialized tools that help enterprises assess and document these potential breaches, ensuring their AI applications remain both secure and compliant.
DynamoFL’s co-Founder Christian Lau emphasized the company’s commitment to facilitating businesses in meeting regulatory developments and deploying LLMs safely. Echoing this sentiment, Greg Thome from Canapi Ventures highlighted the importance of DynamoFL’s approach in addressing data leakage concerns while delivering top-tier AI experiences.
The offerings provided by the company enable organizations to confidentially refine LLMs using their internal data, simultaneously detecting and recording potential privacy concerns. Organizations have the option to either adopt DynamoFL’s comprehensive suite or selectively integrate modules like their Privacy Evaluation Suite, Differential Privacy and/or Federated Learning.
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