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DynamoFL Raises $15.1M Series A to Scale Privacy-Focused Generative AI for the Enterprise

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DynamoFL, Inc. has closed a $15.1 million Series A funding round led by Canapi Ventures and Nexus Venture Partners. The company has raised a total of $19.3 million to meet the demand for its privacy- and compliance-focused generative AI solutions. DynamoFL's flagship technology allows customers to safely train Large Language Models (LLM) on sensitive internal data. The round also had participation from other investors such as Formus Capital, Soma Capital, and angel investors from prominent companies.
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Canapi Ventures and Nexus Venture Partners lead round to help company meet demand for LLM solutions that can safely train on sensitive, internal data

SAN FRANCISCO, Aug. 16, 2023 /PRNewswire/ -- DynamoFL, Inc. today announced that it has closed a $15.1 million Series A funding round to meet demand for its privacy- and compliance-focused generative AI solutions. Coming off a $4.2M seed round, the company has raised $19.3M to date. DynamoFL's flagship technology, which allows customers to safely train Large Language Models (LLM) on sensitive internal data, is already in use by Fortune 500 companies in finance, electronics, insurance and automotive sectors.

The round, co-led by Canapi Ventures and Nexus Venture Partners, also had participation from Formus Capital, Soma Capital and angel investors Vojtech Jina, Apple's privacy-preserving machine learning (ML) lead, Tolga Erbay, Head of Governance, Risk and Compliance at Dropbox and Charu Jangid, product leader at Snowflake, to name a few.

The need for AI solutions that preserve compliance and security has never been greater. LLMs present unprecedented privacy and compliance risks for enterprises. It has been widely shown that LLMs can easily memorize sensitive data from its training dataset. Malicious actors can exploit this vulnerability to extract sensitive users' personally identifiable information and sensitive contract values with carefully designed prompts, posing a major data security risk for the enterprise. The pace of innovation and adoption in the AI sector is punctuated by the rapidly changing global regulatory landscape, many of which require that enterprises detail these data risks, but enterprises today are not equipped to detect and address the risk of data leakage. In the EU, the GDPR and the impending EU AI act, along with similar initiatives in China and India, as well as AI regulation acts in the US, require that enterprises detail these data risks. However, today they are not equipped to detect and address the risk of data leakage.

More clearly needs to be done. As government agencies like the FTC explore concerns around LLM providers' data security, DynamoFL's machine learning privacy research team recently showed how personal information – including sensitive details about C-Suite executives, Fortune 500 corporations, and private contract values – could be easily extracted from a fine-tuned GPT-3 model. DynamoFL's privacy evaluation suite provides out of the box testing for data extraction vulnerabilities and automated documentation to ensure enterprises' LLMs are secure and compliant. 

"We deploy our suite of privacy-preserving training and testing offerings to directly address and document compliance requirements to help enterprises stay on top of regulatory developments, and deploy LLMs in a safe and compliant manner," said DynamoFL co-founder Christian Lau.

"Privacy and compliance are critical to ensuring the safe deployment of AI across the enterprise. These are foundational pillars of the DynamoFL platform," said Greg Thome, Principal at Canapi. "By working with DynamoFL, companies can deliver best-in-class AI experiences while mitigating the well-documented data leakage risks. We're excited to support DynamoFL as they scale the product and expand their team of privacy-focused machine learning engineers."

The company's solutions help organizations privately fine-tune LLMs on internal data while identifying and documenting potential privacy risks. Organizations can choose to implement DynamoFL's end-to-end suite or to implement their Privacy Evaluation Suite, Differential Privacy and/or Federated Learning modules individually.

DynamoFL was founded by two MIT PhDs who have spent the last six years researching the cutting-edge, privacy-focused AI and ML technology forming the basis of the company's core offerings. The team balances expertise in the latest research in privacy-preserving ML, with researchers and engineers from MIT, Harvard and Cal-Berkeley, and experience in deploying enterprise-grade AI applications for Microsoft, Apple, Meta and Palantir, among other top tech companies.

"This investment validates our philosophy that AI platforms need to be built with a focus on privacy and security from day one in order to scale in enterprise use cases," said DynamoFL CEO and co-founder Vaikkunth Mugunthan. "It also reflects the growing interest and demand for in-house Generative AI solutions across industries."

"While AI holds tremendous potential to transform every industry, the need of the hour is to ensure that AI is safe and trustworthy. DynamoFL is set to do just that and enable enterprises to adopt AI while preserving privacy and remaining regulation-compliant," said Jishnu Bhattacharjee, Managing Director, Nexus Venture Partners."We are thrilled to have partnered with Vaik, Christian and team in their journey of building an impactful company."

About DynamoFL, Inc.
DynamoFL is the world's leading enterprise solution for privacy-preserving Generative AI. At DynamoFL we believe that prioritizing privacy, compliance and data security from day 1 while building Generative AI applications is the only way to responsibly scale AI and use it to augment human potential beyond what was thought possible. Our proprietary technology encapsulates state of the art optimization techniques for training and deploying Generative AI models along with a robust privacy training and evaluation suite incorporating paradigms like Federated Learning and Differential privacy to bring high performing end-to-end plug-and-play Generative AI to global enterprises.

About Nexus Venture Partners
Founded in 2006, Nexus Venture Partners is a venture capital firm that supports extraordinary founders in building product-first companies. The firm takes a high-conviction approach, serving as inception, seed, or series-A stage partner to founders, actively engaging with them throughout the company lifecycle. With $2.6 billion capital under management, Nexus focuses on two primary investment areas: enterprise software and AI companies globally and technology-powered businesses within India. For more information, visit https://nexusvp.com/

About Canapi Ventures
Canapi Ventures is a venture capital firm investing in early to growth-stage fintech companies. Our partners have been at the forefront of financial services innovation as operators, investors, bankers, advisors, and regulators. Our venture capital model connects high-quality fintech companies to our extensive network of banks and strategic partners. Canapi Ventures is advised by CenterHarbor Advisors and Canapi Advisors, LLC, a wholly owned subsidiary of Live Oak Bancshares, Inc. (Nasdaq: LOB). For more information, visit http://www.canapi.com.

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SOURCE DynamoFL

FAQ

Who led the Series A funding round for DynamoFL, Inc.?

Canapi Ventures and Nexus Venture Partners led the Series A funding round for DynamoFL, Inc.

How much funding did DynamoFL, Inc. raise in the Series A round?

DynamoFL, Inc. raised $15.1 million in the Series A funding round.

What is DynamoFL's flagship technology?

DynamoFL's flagship technology allows customers to safely train Large Language Models (LLM) on sensitive internal data.

Which sectors are already using DynamoFL's technology?

Fortune 500 companies in finance, electronics, insurance, and automotive sectors are already using DynamoFL's technology.

Who are some of the investors in DynamoFL's funding round?

Some of the investors in DynamoFL's funding round include Formus Capital, Soma Capital, Vojtech Jina (Apple's privacy-preserving ML lead), Tolga Erbay (Head of Governance, Risk and Compliance at Dropbox), and Charu Jangid (product leader at Snowflake).

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