DeepKeep
Enhances AI security, detects risks, automates remedies.. [Contact for Pricing]
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What is DeepKeep?
DeepKeep is an AI-native Security and Trust Platform that comprehensively addresses security risks and inference trust issues for AI, LLM, and computer vision models. The platform provides end-to-end security from the research and development phase of machine learning models through risk assessment, prevention, detection, and mitigation all the way to real-time deployment and use.
Key features include AI Firewall with over 60 built-in guardrails for real-time protection, AI Red Teaming (including the new Vibe AI Red Teaming for human-steered dynamic testing), AI Lens for visibility and access control, AI Agent Scanner for monitoring AI agents, and Model Scanning for securing the AI supply chain. The platform protects against prompt injection, adversarial manipulation, semantic attacks, hallucinations, data leakage, PII exposure, toxicity, and bias while ensuring compliance with GDPR, CCPA, LGPD, and other global regulations.
DeepKeep is designed for enterprises across finance, healthcare, automotive, technology, and government sectors that use AI applications, agentic AI, AI applications with MCP, and employees making daily use of LLMs. It serves cybersecurity teams, security engineers, CISOs, AI developers, and compliance teams who need to secure AI systems from development through production.
DeepKeep pricing
Pricing model: Freemium
DeepKeep is not a free tool. It is a commercial product with customized pricing tailored to each organization's specific needs and scale. Exact pricing details are not publicly disclosed. On AWS Marketplace, DeepKeep Automated AI Red Teaming is available as a 12-month contract at $5,000,000 for a single LLM model risk assessment license. New users can request a demo or consultation at https://www.deepkeep.ai/book-demo. Existing customers can enable new capabilities like the PII guardrail directly within their dashboard.
DeepKeep pros
- AI-native security platform specifically designed for AI/LLM protection
- Over 60 built-in AI guardrails in the AI Firewall
- Closed-loop security connecting model evaluations with firewall protection
- Supports multiple model types: LLM, Vision, Multimodal, and tabular data
- Vibe AI Red Teaming enables human-steered dynamic testing with natural language commands
- Real-time alert triggering in pre-deployment and post-deployment environments
- Detects and prevents prompt injection, jailbreaks, and adversarial attacks
- Identifies and alerts against hallucinations using hierarchical data sources
- PII guardrail detects, redacts, and blocks personal data in prompts and responses
- Context-aware security solutions for more realistic and adaptive protection
- Multilingual support with native multiple language capabilities
- AI Agent Scanner provides visibility and control over enterprise AI agents
- Model Scanning ensures AI supply chain provenance and compliance
- Remediation guidance with clear actionable recommendations for each finding
- CI/CD integration with scheduled tests and event-driven re-scans
- Industry-leading accuracy for PII protection across global regulations
- End-to-end platform from development phase through product lifecycle
DeepKeep cons
- Pricing is not publicly disclosed and requires custom enterprise quotes
- Platform is complex and requires technical expertise to use effectively
- Best suited for large organizations rather than small businesses
- Resource-intensive and costly implementation
- Interface leans towards technical users rather than non-technical stakeholders
- Limited public information about specific pricing tiers and support options
- No free tier available - commercial product only
- May be overkill for organizations with simple AI use cases
Frequently asked questions about DeepKeep
What is DeepKeep?
DeepKeep is the AI-native Security Platform that builds trust by applying security across the entire AI lifecycle from development to real-time use. It safeguards AI with security and trustworthiness from the research and development phase of machine learning models through risk assessment, prevention, detection and mitigation. The platform addresses security risks and inference trust issues for AI, LLM, and computer vision models.
What does the AI Firewall do?
The AI Firewall is part of DeepKeep's extensive suite with over 60 built-in AI guardrails that provide continuously updated, real-time alert triggering throughout pre-deployment and post-deployment environments. It protects against LLM attacks including prompt injection, adversarial manipulation and semantic attacks, safeguards against data leakage and PII exposure, and detects toxic or discriminatory language.
What is Vibe AI Red Teaming?
Vibe AI Red Teaming is DeepKeep's first-of-its-kind capability designed for human-steered, dynamic testing and attack simulation on AI applications and AI agents. It enables security teams to guide execution according to their domain knowledge using natural language commands, refine attacks in real time, select attack types and depth, define testing objectives, and introduce custom scenarios mid-execution. It bridges agent-driven execution with human-steered commands beyond automated red teaming.
How does DeepKeep protect against hallucinations?
DeepKeep identifies and alerts against hallucination using a hierarchical system of data sources, including both internal and trusted external references. A hallucination occurs when a model's response contains inaccurate information, producing outputs that are nonsensical, misleading, or irrelevant. The platform detects these issues and provides remediation guidance.
What AI agents can DeepKeep secure?
DeepKeep for AI Agents monitors, evaluates, and controls AI agents across the enterprise. It scans for vulnerabilities, enforces guardrails, secures orchestration, and manages MCP gateways with real-time visibility and protection. The platform identifies which MCP servers are being used, recommends whether to allow or block them, and helps enforce consistent policy while highlighting vulnerabilities and unsafe design patterns.
Does DeepKeep support multiple model types?
Yes, DeepKeep has multi-model support for diverse models including LLM, Vision, and Multimodal systems. It is the only platform addressing physical security and supports computer vision models alongside language models. The AI Red Teaming capability is model-agnostic and supports both LLMs and computer vision models for consistent evaluation across multimodal AI systems.
What regulations does DeepKeep ensure compliance with?
DeepKeep ensures ongoing compliance with worldwide AI, cybersecurity and privacy regulations. The PII guardrail specifically supports global data protection laws including Europe's GDPR, California Consumer Privacy Act (CCPA), Brazil's LGPD, and PIPA in South Korea. The platform helps enterprises meet regulatory requirements while protecting personal data in AI workflows.
How does Model Scanning work?
Model Scanning secures the AI supply chain with static and dynamic scanning to guarantee provenance, compliance and operational safety. It protects against poisoning when hackers purposely change a model or dataset, and verifies the integrity of AI models throughout the development and deployment lifecycle.
What is AI Lens?
AI Lens provides visibility, access control, and run-time protection for how employees and developers interact with AI systems across the enterprise. It gives organizations insight into AI usage patterns and enables control over access to AI systems while protecting against misuse during daily work activities.
Is DeepKeep suitable for small businesses?
DeepKeep is best suited for large organizations and enterprises. The platform is complex and requires technical expertise, making it more appropriate for financial institutions, technology companies, healthcare organizations, automotive companies, and government agencies that have significant AI infrastructure and dedicated security teams. It is a resource-intensive and costly solution designed for organizations with complex AI security needs.