DeepKeep — AI Security Software

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What is DeepKeep?

DeepKeep is an AI-Native Security platform that protects AI applications for large corporations using AI, GenAI, and LLM. It safeguards AI throughout its lifecycle, from risk assessment to threat prevention, helping companies create bold AI models while defending against data leakage and toxic responses.

What sets DeepKeep apart?

DeepKeep sets itself apart with its AI-Native security platform, specifically designed to safeguard the entire AI lifecycle for corporations integrating advanced AI technologies. This comprehensive protection is valuable for businesses aiming to push the boundaries of AI innovation while maintaining robust security measures. By enabling the creation of bold AI models without compromising on safety, DeepKeep offers a unique approach to balancing AI advancement and risk management.

DeepKeep Use Cases

AI model risk assessment
LLM security protection
Data leakage prevention
Bias detection in AI
AI trustworthiness evaluation

Who uses DeepKeep?

Machine Learning Engineers Dev Ops Engineers IT Project Managers Compliance Managers Risk Analysts Chief Technical Officers Security Engineers Data Scientists Cybersecurity Specialists

Features and Benefits

AI-Native Security
Safeguards AI applications throughout their entire lifecycle, from development to deployment, using AI-powered protection against various threats and vulnerabilities.
Risk Assessment Module
Evaluates AI model resilience through penetration testing, identifying potential vulnerabilities in security, trustworthiness, and privacy.
Continuous Monitoring
Provides real-time alerts and protection against attacks on AI applications, covering a wide range of security and safety categories.
Multi-Modal Protection
Secures various AI modalities including Large Language Models (LLMs), computer vision, and tabular data models.
Compliance and Ethics Checks
Detects and mitigates issues related to bias, fairness, toxicity, and data leakage to ensure AI models meet ethical and regulatory standards.