- Access Control
- AI-Driven
- AI Security
- Application
- Application Security Testing
- Artificial Intelligence
- Compliance
- Cybersecurity
Show all 28 topics
- Data Loss Prevention
- DevSecOps
- Enterprise
- Generative AI
- Identity Access Management
- IT Governance
- Large Language Model
- Least Privilege
- Microservices
- Monitoring
- Observability
- Orchestration
- Platform Engineering
- Protection
- Risk Management
- Security Operations
- Software
- Standards
- System Integration Testing
- Visibility
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Who is Kipling Secure?
Kipling Secure is a cybersecurity company that develops tools and workflows for securing Large Language Model (LLM) applications and AI-driven software systems in enterprise environments.
- Security controls and guardrails for LLM and Generative AI (GenAI) applications (application security)
- Scanning and policy enforcement for Artificial Intelligence (AI) prompts, responses, and integrations (security governance)
- Monitoring of LLM usage for data exposure, compliance, and behavioral policy violations (security monitoring)
- Developer-focused tooling to integrate AI security checks into existing software delivery pipelines (DevSecOps)
- Frameworks and playbooks for aligning AI application behavior with enterprise security and compliance requirements (governance and risk management)
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More About Kipling Secure
Kipling Secure focuses on security for LLM and GenAI applications deployed within enterprises, treating these systems as a new application security and governance surface. Its offerings are positioned for security teams, platform engineering groups, and application owners who embed LLMs into products, internal tools, and workflows. The company emphasizes systematic control over what prompts and data reach AI models, how models respond, and how those responses are consumed by downstream applications.
The platform is aligned with enterprise security concepts such as policy-based access control, data classification, and least-privilege principles applied to AI interactions. In practice, this includes guardrails that constrain prompts and responses according to configurable rules, filters, or policies, as well as mechanisms to block or modify model interactions that conflict with organizational security standards. These capabilities map to categories such as application security, Data Loss Prevention (DLP), and security governance for AI workloads.
Kipling Secure tools are designed to run alongside existing LLM providers and orchestration frameworks rather than replace them. They can System Integration Testing (SIT) between client applications and external or internal LLM endpoints, enforcing rules before prompts are sent and after responses are returned. This intermediary architecture allows security teams to introduce content checks, redaction, policy validation, and logging without modifying the underlying model infrastructure. The approach is compatible with common API-based LLM integrations and can be incorporated into service-oriented and microservices architectures.
From a DevSecOps perspective, Kipling Secure supports integration of AI security checks into software development and deployment workflows, so that AI-related risks are addressed during design, build, and release stages rather than only in production. This may include configuration of environment-specific policies, pre-deployment validation of AI workflows, and runtime monitoring of usage patterns. Output logs and analytics can be routed into existing Security Information and Event Management (SIEM) tools or observability stacks, giving Security Operations (SecOps) centers additional visibility into AI-related events.
In the enterprise security marketplace, Kipling Secure aligns with solution categories such as AI security, LLM application security, and governance for GenAI. Organizations can use it to apply consistent policies across multiple AI providers and models, establish standardized guardrails for business units experimenting with AI, and document controls for regulatory or compliance reporting. Its focus on policy, monitoring, and integration positions it as a component of broader security architectures that include identity and access management, data protection, and traditional Application Security Testing (AST).
Our description of Kipling Secure. Updated December 2025.
