DataAnonymiser helps individuals and organizations use AI without exposing sensitive information. For individuals, it detects and replaces PII in text, PDFs, and images directly on-device before data is shared with tools like ChatGPT, Claude, or Copilot. For enterprises, it provides an AI DLP platform that monitors and protects sensitive data across AI tools and connected services.
DataAnonymiser was born out of a problem we encountered while building another AI-powered product.
To achieve the level of accuracy our product required, we needed to integrate with frontier AI models rather than host models entirely within our own infrastructure. This introduced an important privacy challenge: unless users carefully removed sensitive information from the documents, files, and prompts they submitted, that data could be unintentionally shared with third-party AI providers.
We built DataAnonymiser to solve this problem.
DataAnonymiser provides local, on-device anonymization and redaction, allowing sensitive information to be removed before it ever reaches an external AI service. It works across text, images, documents, and other files, automatically detecting sensitive information and replacing it with meaningful placeholders while preserving the context needed for AI systems to remain useful.
We also offer browser extensions that detect and redact personally identifiable information in real time when users interact with web-based AI tools.
For conversational AI, DataAnonymiser goes a step further with reversible prompt anonymization. Sensitive information is replaced with placeholders before a prompt is sent to a generative AI service. Once the response is returned, DataAnonymiser securely restores the original information locally, allowing users to benefit from powerful AI models without unnecessarily exposing sensitive data.
For organizations, we provide enterprise AI Data Loss Prevention (DLP) solutions that extend these protections across a wide range of applications and services. This gives companies greater visibility and control over how sensitive data is used with generative AI, while enabling employees to adopt AI tools more safely.
Our goal is simple: make powerful AI usable without forcing users and organizations to compromise on data privacy.
Why We Built DataAnonymiser
DataAnonymiser was born out of a problem we encountered while building another AI-powered product.
To achieve the level of accuracy our product required, we needed to integrate with frontier AI models rather than host models entirely within our own infrastructure. This introduced an important privacy challenge: unless users carefully removed sensitive information from the documents, files, and prompts they submitted, that data could be unintentionally shared with third-party AI providers.
We built DataAnonymiser to solve this problem.
DataAnonymiser provides local, on-device anonymization and redaction, allowing sensitive information to be removed before it ever reaches an external AI service. It works across text, images, documents, and other files, automatically detecting sensitive information and replacing it with meaningful placeholders while preserving the context needed for AI systems to remain useful.
We also offer browser extensions that detect and redact personally identifiable information in real time when users interact with web-based AI tools.
For conversational AI, DataAnonymiser goes a step further with reversible prompt anonymization. Sensitive information is replaced with placeholders before a prompt is sent to a generative AI service. Once the response is returned, DataAnonymiser securely restores the original information locally, allowing users to benefit from powerful AI models without unnecessarily exposing sensitive data.
For organizations, we provide enterprise AI Data Loss Prevention (DLP) solutions that extend these protections across a wide range of applications and services. This gives companies greater visibility and control over how sensitive data is used with generative AI, while enabling employees to adopt AI tools more safely.
Our goal is simple: make powerful AI usable without forcing users and organizations to compromise on data privacy.