SecurePrompt is a revolutionary wrapper application that prioritizes user privacy in the age of generative AI. Our innovative solution detects and masks sensitive data, ensuring your information remains confidential when interacting with public large language models.
Multi-Model Support: Search across various generative AI models, including Meta, OpenAI ChatGPT, Google Gemini, Anthropic Claude, CoHere, and more
Real-time Data Masking: Instantly detect and protect sensitive information before it's shared with external models
User-Specified Models: Integrate custom models tailored to your specific needs
Robust Security Measures: End-to-end encryption, secure data storage, and regular security audits
User Input: You interact with SecurePrompt's intuitive interface, asking questions or providing data
Data Detection: Our advanced algorithms identify sensitive information in real-time
Masking and Encryption: SecurePrompt masks and encrypts sensitive data, ensuring confidentiality
Model Interaction: Our wrapper application communicates with the chosen generative AI model
Results: You receive accurate and informative responses without compromising your privacy
Unparalleled Privacy: Protect sensitive information from external exposure
Seamless Integration: Easily switch between various generative AI models
Customization: Tailor SecurePrompt to your specific needs with user-specified models
Data masking replaces sensitive data with anonymized data to protect private information and comply with privacy requirements. Data masking is particularly useful in ensuring you’ve eliminated all personally identifiable information like names, phone numbers and addresses, when writing AI prompts.
Toxicity detection is a method of flagging toxic content such as hate speech and negative stereotypes. It does this by using a machine learning (ML) model to scan and score the answers an LLM provides, ensuring that generations from a model are usable in a business context.
Zero retention means that no customer data is stored outside of Salesforce. Generative AI prompts and outputs are never stored in the LLM, and are not learned by the LLM. They simply disappear.
Auditing continually evaluates systems to make sure they are working as expected, without bias, with high quality data, and in-line with regulatory and organizational frameworks. Auditing also helps organizations meet compliance needs by logging the prompts, data used, outputs, and end user modifications in a secure audit trail.