DeepKeep for LLM
AI-native security and trustworthiness for large language models enabling enterprises to leverage LLMs in a secure, risk-free way.
Picari insights
Enterprise security and engineering teams building or deploying production-grade LLM applications and autonomous agents that require end-to-end vulnerability scanning, automated red teaming, and runtime guardrails.
- Automated red teaming and penetration testing for LLMs
- Real-time guardrails and runtime prompt injection defense
- Pre-deployment vulnerability scanning for multi-agent AI architectures
- Traditional application security without dedicated generative AI or LLM components
- Organizations using out-of-the-box SaaS tools without custom LLM pipelines or APIs
- Teams needing basic static application security testing (SAST) or software composition analysis (SCA)
Ask about pricing, alternatives, or if DeepKeep for LLM is right for you.
- Personalized fit analysis
- See relevant alternatives
- Run an evaluation when you're ready
Core capabilities
Common use cases
Autonomous AI workflows and agents
Customer-facing AI applications with guardrails
Securing internal LLM chatbots
Things to consider
Every product has trade-offs, and which of them matter depends on your environment, your team and your timeline.
Security & compliance
Frameworks DeepKeep for LLM reports for security, privacy, and regulatory compliance.
SOC 2 Type II
AICPA security & availability audit
ISO/IEC 27001
Information security management standard
GDPR
EU data protection compliance
DeepKeep for LLM pricing and integrations
For DeepKeep for LLM integration and pricing details, ask Picari. Start a briefing with your question, such as whether it connects to your SIEM, identity provider and ticketing stack, or how it is priced at your seat count and data volume.
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Profile last updated on 28 September 2026 by the vendor, DeepKeep.