AI Data Defense provides a real‑time data protection layer that intercepts and sanitizes prompts and responses for generative AI models. It masks, tokenizes, and redacts PII, blocks injection and poisoning attacks, and generates audit‑ready logs to meet GDPR, CCPA, HIPAA and similar regulations. The API‑first platform integrates with any LLM endpoint, supports multi‑tenant isolation, and offers a centralized dashboard for policy management and compliance reporting.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations using generative AI models—whether public LLMs like ChatGPT or private deployments—risk exposing personally identifiable information (PII), proprietary data, and intellectual property. Unfiltered prompts can also be vulnerable to injection attacks and data poisoning, leading to compliance violations and reputational damage.
Solution
AI Data Defense delivers a real-time data protection layer that intercepts every AI request and response, automatically masking, tokenizing, and redacting sensitive content. The platform enforces configurable policies to block prompt injection and detect data poisoning, while generating audit‑ready logs that satisfy GDPR, CCPA, HIPAA, and similar regulations. It integrates with any LLM endpoint via API, supports multi‑tenant isolation for separate projects, and provides a centralized dashboard for monitoring, policy management, and compliance reporting. Deployment is lightweight and can be added to existing workflows without modifying the underlying AI models.
Target Audience
The primary customers are enterprises, managed service providers, and R&D teams that incorporate generative AI into business processes, as well as SMBs and marketing agencies seeking secure, compliant AI usage.
Features
- Real‑time PII detection and redaction with tokenization and masking applied to inbound prompts and outbound responses
- Built‑in prompt‑injection and data‑poisoning filters that reject malicious inputs before they reach the model
- API‑first integration compatible with public LLMs (e.g., ChatGPT, Claude) and private model deployments
- Multi‑tenant architecture ensuring data segregation and secure isolation for different teams or projects
- Granular admin console with dashboards, usage analytics, and role‑based access controls
- Compliance‑grade audit logs and exportable reports aligned with GDPR, CCPA, HIPAA, and other standards
- Optional SIEM connectors and webhook support for enterprise security monitoring
- Flexible billing options including monthly, annual, or credit‑based plans to match usage patterns