en.Wedoany.com Reported - On May 13, 2026, San Francisco-based privacy technology startup Secludy announced the official launch of its privacy protection platform, simultaneously completing a $4 million seed funding round. The platform is purpose-built for banks, payment companies, and fintech enterprises, enabling them to train generative AI models and evaluate AI vendors without exposing real customer data. The round was led by Impression Ventures, with participation from LAUNCH, The Syndicate, Wedbush Ventures, Precursor Ventures, Hustle Fund, Script Capital, Mana Ventures, and Chispa VC. The funds will be used to accelerate product promotion and expand coverage of enterprise AI workflows.
Secludy was co-founded by CEO Ben Cerchio and CTO Ming He. Cerchio brings years of experience in privacy and information security, having previously led product privacy efforts at TikTok and, earlier, worked on information security compliance at PayPal. Co-founder and CTO Ming He holds a Ph.D. in computational biology with a specialization in machine learning. At the launch event, Cerchio stated bluntly: "Every CEO is demanding their teams deploy AI, but no one wants to explain a customer data breach on the next earnings call. The proprietary data that builds the strongest models is precisely the forbidden zone data teams can't touch. We created Secludy to break this dilemma."
The financial industry faces widespread data privacy barriers when implementing large language models. Highly sensitive core data such as transaction records, anti-fraud models, customer service logs, and credit files have long been difficult to use for model training and vendor evaluation due to strict limitations imposed by privacy regulations, customer contracts, and cross-border data flow rules. Secludy's platform acts as a control layer between enterprise AI and privacy, legal, and security reviews, helping compress vendor evaluation processes that often required months of legal review down to just weeks, shifting privacy teams from passive rejection to conditional approval.
The platform leverages differential privacy technology to generate synthetic data that is highly consistent with the statistical characteristics of the original dataset but stripped of sensitive information. The resulting synthetic data can be used by teams to train, fine-tune, and evaluate AI models without exposing real customer information. The platform's foundational architecture is built with compliance standards such as GDPR, CCPA, and HIPAA embedded from the ground up, and it is deployed entirely within the customer's own cloud environment, ensuring full control over data sovereignty. Secludy's core logic lies in breaking the predicament where "data is most valuable yet most untouchable," constructing an auditable privacy assurance mechanism.
From an industry demand perspective, the privacy-enhancing technology market is in a phase of rapid expansion. According to market research data, the global privacy-enhancing technology market size is projected to grow from $4.33 billion in 2025 to $5.52 billion in 2026, representing a compound annual growth rate of 27.4%. Demand for data anonymization technologies in the financial services sector is also growing rapidly, with the market size expected to rise from $1.76 billion in 2025 to $2.04 billion in 2026, a compound annual growth rate of 16.2%. Secludy is targeting precisely this vertical track with the most rigid demand and the highest compliance barriers.
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