Secludy, a privacy-tech startup serving banks, payments firms, and fintech companies, launched their platform for financial services companies that need to train GenAI models and evaluate AI vendors without exposing real customer data. Secludy just closed $4 million in seed funding to accelerate the rollout.
Impression Ventures, a fintech-focused venture firm, led the round. LAUNCH and The Syndicate, a venture firm and angel investing group led by Jason Calacanis, also joined, along with Wedbush Ventures, Precursor Ventures, Hustle Fund, Script Capital, Mana Ventures, and Chispa VC.
Every major financial services company now has a mandate from the top to ship generative AI. The models that matter most are trained on proprietary data. Transaction histories, fraud patterns, customer support logs, loan files. That data rarely flows outside of data silos. Privacy laws, customer contracts, and cross-border rules keep it locked down. The same barriers show up when firms want to share data with AI vendors during evaluations and pilots, which is where most enterprise GenAI deals get stuck.
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Secludy is building the control layer between enterprise AI and the privacy, legal, and security work that must be cleared before anything ships. The platform lets AI teams move fast without putting the company at risk and gives privacy and security teams a way to say yes instead of no. Programs that took six months of review move in days, and models hit performance bars that legacy approaches could never support.
“Every CEO is telling their teams to ship AI. None of them want to be the one explaining a customer data leak on the next earnings call,” said Ben Cerchio, founder and CEO of Secludy. “The data that would make these models most powerful is exactly the data teams can’t touch. We built Secludy to close that gap and give every enterprise a path to using their own data safely.”
Cerchio spent his career in privacy and information security, most recently in product privacy at TikTok and earlier in InfoSec compliance at PayPal. He saw the same pattern across regulated industries. AI gets blocked by privacy, legal, and third-party contract review. He started Secludy to fix the layer underneath.
Secludy unblocks vendor evaluations, where many enterprise GenAI deals get stuck. A fintech company testing whether an AI vendor can improve fraud analysis or customer support typically stalls in legal review before a single model runs. With Secludy, those evaluations proceed on realistic data without exposing real customer records, compressing a process that typically takes months into weeks.
“Working with our LPs and portfolio companies, we keep hearing the same thing from banks and insurers: they’re sitting on decades of proprietary data and know they need to train models on it, but can’t do it safely. That’s the gap Secludy closes. We led this round because every regulated data holder is going to need this, and this is the team to ship it,” said Christian Lassonde, Managing Partner at Impression Ventures.
The Secludy team brings deep technical and privacy expertise. Co-founder and CTO Ming He holds a PhD in computational biology with a machine learning specialization. He previously conducted postdoctoral research at Stanford Research Institute and built enterprise AI solutions at Williams-Sonoma.
“Ben and Ming have lived this problem from inside PayPal, TikTok, and enterprise AI, and built Secludy around the reality of how privacy review actually works. That combination of technical depth and firsthand founder insight was compelling to us,” said Petra Griffith, Managing Partner at Wedbush Ventures.
Fintech is Secludy’s initial focus, where privacy, legal, and cross-border restrictions hit hardest. Fraud models, customer-facing assistants, and internal AI tools all face the same barriers. For banks operating across multiple countries, cross-border data transfer rules compound the problem further. The platform is available now for banks, payments firms, and fintech companies, with healthcare, life sciences, and other regulated industries launching next.
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