Secure your databases before they reach LLMs. Prevent the BodySnatcher Effect and stay GDPR compliant while scaling your AI agents.
Raise-ready
Enterprise Trust & DACH Compliance Technical maturity signals for accelerator committees — details to follow.
Why exposing raw enterprise data to AI pipelines is no longer acceptable.
Queries and context sent to models can echo sensitive rows, schema hints, and business logic—recoverable across sessions and providers.
Once production data shapes agent behavior, copies of identity and patterns propagate—hard to unwind and impossible to fully retract.
Cross-border flows, purpose limitation, and audit trails buckle when every AI touchpoint sees identifiers you cannot legally justify.
How AnonifyDB puts a controlled boundary between databases and AI workloads.
Sit between apps and data stores to enforce policy per connection, tenant, and workload—without fork-lifting your stack.
Strip or tokenize PII while preserving joins, aggregates, and semantics so models stay useful—not naive redaction.
Wire credentials through the proxy and route traffic—no application rewrites required for a first defensive perimeter.
Governance and deployment patterns aligned with European enterprise expectations.
Data minimization, purpose limitation, and residency-aware processing designed around EU regulatory interpretation—not checkbox PDFs.
Assume breach at every hop: authenticate callers, authorize scopes, and log access so security teams can prove who saw what.
Package and operate as a managed application so procurement, billing, and isolation match how enterprises already buy cloud software.