01 · Monitor every inference call
Prompt-level and response-level traffic is monitored 24x7 across both direct-call applications and MCP-based agentic applications.
Secure your AI agents, MCP servers, LLM data pipelines and AI SOC.
Continuous compliance across DPDP, MAS TRM and NESA.
Control every identity. Secure every access.
Know your data. Protect what matters.
Secure cloud, apps and APIs from build to run.
Secure every connection, from cloud to factory
Detect threats faster. Respond in minutes.
AI Security
24x7 monitoring and real-time blocking of prompt injection, jailbreak attempts and sensitive output, at the inference layer, for both direct-call and agentic applications.
The challenge
Approach
01 · Monitor every inference call
Prompt-level and response-level traffic is monitored 24x7 across both direct-call applications and MCP-based agentic applications.
02 · Block in real time
Prompt injection and jailbreak attempts are detected and blocked inline, at the inference edge, not just flagged after the fact using AI-driven behavioral analytics and adaptive policy enforcement continuously.
03 · Triage and report
Incidents are triaged within SLA, with monthly operations reporting and quarterly tuning to keep pace with new attack techniques through continuous threat intelligence updates, policy refinement, and optimization.
How it works
What’s included
Outcomes
Why Gruve
A firewall around your AI application does nothing if the attack happens inside the prompt and response itself. This service monitors that inference layer around the clock, for both traditional and agentic applications, and blocks injection and jailbreak attempts inline instead of just logging them for later review.
Organizations that want prompt-level and response-level threats blocked in real time
Organizations relying on network and endpoint security alone to protect AI applications
24x7 inference-layer monitoring operated across your AI applications
No dedicated monitoring at the point where prompts and responses actually flow
Injection and jailbreak attempts blocked inline, at the inference edge
Attacks discovered only if they cause a visible downstream problem
Coverage extended to MCP-based agentic applications
Agentic applications left unmonitored at the inference layer entirely
Real-time output filtering for sensitive content
Sensitive output reaches the user before anyone reviews it
AI Security
Analysis of your AI estate combining a baseline inventory, adversarial red team testing and a model builder pipeline review.
Learn more →Classification, DLP policy and audit logging for the data flowing through AI prompts and responses.
Learn more →Operation of a maintained AI governance register and control mapping against your chosen frameworks.
Learn more →Testimonials
The partnership with Gruve brings significant value to customers by combining thought leadership, delivery, and execution of services. Leveraging AI/ML and Cloud tools in delivering software integrations and services can significantly ease transitions for large enterprise organizations.
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Stop AI threats the moment they happen. Talk to us about managed runtime protection for your models.
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