Safeguard data privacy while retaining usability. Our intelligent data tokenization technique delivers the highest data privacy and security while ensuring usability of your tokenized data.
Selectively isolate PII from your data sets and replace it with unique non-identifiable tokens, while maintaining the structure and integrity of the remaining data.
Consistently tokenize PII across various data sources and store the tokens in a secure Vault. Perform accurate data analysis and AI/ML model training with the tokenized data.
Preserve the original format of the dataset, with the flexibility of masking data in a format of your choice. Maintain the same consistent format across various data sources.
Unlock the potential of your enterprise data while upholding data privacy. Ensure usability of your masked data by tokenizing sensitive information consistently across your data sources. Generate insights by aggregating and analyzing masked data across multiple data sources.
Replace sensitive PII data with tokens that have no inherent meaning or value. Ensure that a piece of sensitive information sitting across data sources is always replaced with the same token. Enable secure data storage and transmission without exposing sensitive details.
Enable easier data integration and interoperability by consistent tokenization. Simplify data exchange, data synchronization, and integration efforts between various systems. Confidently share data between stakeholders without worrying about data privacy.
Adhere to privacy requirements by reducing the amount of sensitive information that is stored and processed. This allows for better data obfuscation while minimizing the risk of data breaches and unauthorized access.
Derive insights from the tokenized data while preserving the privacy and security of the original data. Perform computations, statistical analysis, and predictive modeling without the need to access sensitive data.
Mask PII from production data when creating test data for development and testing. This prevents accidental exposure of sensitive information and ensures a safer development environment.
Harness the power of generative AI, Large Language Models (LLMs), and other publicly hosted AI models without compromising data privacy and security.
Because we're transforming the way you safeguard sensitive information with cutting-edge technology. We are taking a giant leap forward on helping you protect and unlock your data with intelligent data tokenization. Identify PII, monitor and mitigate data privacy risks with the power and simplicity of Protecto.
Our turnkey APIs are designed for seamless integration with your existing systems and infrastructure, enabling you to go live in days.
Deliver data tokenization in real-time and scale effortlessly to accommodate high data volumes without compromising on performance.
Derive value quickly by connecting select data sources. Avail our simplified pricing model as you protect additional data sources.
Our intuitive user interface provides guided workflows to help you quickly navigate through the configuration and get started in days.
Lock your sensitive PII in a zero-trust secure data privacy vault, that provides a robust solution to store and manage sensitive PII securely.
In the domain of data security, "tokenization" refers to the process of substituting sensitive or regulated information, such as personally identifiable information (PII) or credit card numbers, with a non-sensitive counterpart known as a token. This token holds no intrinsic value and serves as a representation of the original data. The tokenization system keeps track of the mapping between the token and the sensitive data stored externally. Authorized users with approved access can perform tokenization and de-tokenization of data as required, ensuring secure and controlled handling of sensitive information.
Tokenization involves replacing sensitive data with a token or placeholder, and the original data can only be retrieved by presenting the corresponding token. On the other hand, Encryption is the process of transforming sensitive data into a scrambled form, which can only beread and understood by using a unique decryption key
To enable various business objectives, such as analyzing marketing metrics and reporting, an organization might need to aggregate and analyze sensitive data from various sources. By adopting tokenization, an organization can reduce the instances where sensitive data is accessed and instead show tokens to users that are not authorized to view sensitive data. This approach allows multiple applications and processes to interact with tokenized data while ensuring the security of the sensitive information remains intact.
No, tokenization is a widely recognized and accepted method of pseudonymization. It is an advanced technique for safeguarding individuals' identities while preserving the functionality of the original data. Cloud-based tokenization providers offer organizations the ability to completely eliminate identifying data from their environments, thereby reducing the scope and cost of compliance measures.
Tokenization is commonly used as a security measure to protect sensitive data while still allowing certain operations to be performed on the data without exposing the actual sensitive information. Various types of data like credit card data, Personal Identifiable Information (PII), transaction data, Personal Information (PI), health records, etc. can be tokenized.
Real-time token generation happens in sub-seconds. This implies that the tokenization algorithm or method used is highly efficient and can handle large volumes of text in real-time applications without causing significant delays or bottlenecks.
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