This company offers an API that detects and removes harmful content from text data using toxicity detection, sentiment analysis, and topic modeling. Their tools enable businesses to clean and analyze large datasets for offensive language, hate speech, and other unwanted content.
Funding
Funding not disclosed
Founders
Product
Problem
Large language models (LLMs) and AI agents are vulnerable to exploitation through prompt injection, toxicity, misuse, and data leakage, leading to unreliable and unsafe AI applications. Existing security solutions are often inadequate for testing and mitigating these emerging GenAI threats.
Solution
Detoxio AI provides an AI red teaming platform that enables continuous testing and security for GenAI agents throughout the AI agent lifecycle. The platform simulates adversarial threats, tests for vulnerabilities, and deploys guardrails to ensure safety, compliance, and resilience. Detoxio AI helps organizations to build safe AI agents faster, without compromising on security or performance, by integrating with AI platforms, GitHub, and CI/CD pipelines for automated testing and real-time monitoring.
Target Audience
Detoxio AI targets AI engineers, cybersecurity professionals, and enterprises building and deploying GenAI applications who need to ensure the security, safety, and compliance of their AI systems.
Features
- AI Red Teaming: Tests for over 32 categories related to toxicity, misuse, and data leaks, with capabilities to generate, run, and evaluate tests.
- AI Guardrails: Designs and deploys AI filters, guardrails, and data leak prevention mechanisms.
- CI/CD Integration: Integrates with cloud environments to run AI security tests as part of MLOps pipelines.
- OWASP Top 10 LLM Apps Testing: Simulates critical attacks like prompt injections, system prompt leaks, and hallucinations to uncover vulnerabilities.
- AI Firewall: Creates and enforces AI-specific security controls to detect malicious prompts and block data exfiltration attempts.
- Autonomous Jailbreak Agent: Simulates real-world jailbreak prompts to rigorously test the defenses of AI agents and LLMs.
- Tactic-Driven Framework: Employs modular strategies like roleplay and prompt obfuscation to stress-test models.
- Provider Agnostic: Supports various models, including OpenAI, Hugging Face, and custom web apps, through its provider architecture.
- Dataset Integration: Bundled with risk datasets like HF_HACKAPROMPT, STRINGRAY, and AIRBENCH for jailbreaks, toxicity, and misinformation.