Elevate Private AI: A Safe Gateway for LLM Interactions
Maintain full control and compliance for enterprise AI solutions while delivering powerful LLM-driven experiences in a protected environment.
Gain full visibility into each AI request and response, capturing prompts, context, retrieved chunks, and LLM outputs. Monitor latency, tokens, application usage, and dataset references in a single, unified dashboard for complete oversight.
Assign unique keys to applications and individual users for precise tracking and governance. Capture granular usage metrics, manage model access, and maintain comprehensive control over LLM consumption across your organization.
Enhance LLM accuracy with real-time RLHF data collection and direct feedback management. Export curated datasets for ongoing fine-tuning, refining models based on genuine user interactions, domain knowledge, and enterprise-specific requirements.
Aggregate key metrics across every deployment—such as jailbreak attempts, toxicity levels, latency, and request volumes—and generate tailored reports. Track drift, measure app utility, observe cache usage, and perform data clustering for deeper performance insights.
Configurable Guardrails
Protect proprietary data with integrated guardrails, scanning inputs and outputs. Configure custom rules for PII, jailbreak attempts, and toxicity.
Real-Time Threat Detection
Identify suspicious behaviors and unauthorized requests instantly, preventing data leaks and ensuring secure LLM interactions at scale.
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Granular Access Policies
Set dynamic permissions for roles, teams, or projects. Control LLM usage precisely without hindering innovation or performance.
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Customizable Compliance Framework
Tailor SecureLLM to address complex enterprise mandates, ensuring continuous alignment with industry regulations, auditability, and internal security policies.
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Instant Audit Trails
Track every user action and model response, ensuring a transparent log for investigation, policy enforcement, and accountability.
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Secure Model Lifecycle Management
Deploy, manage, and monitor models within a robust security framework, maintaining enterprise-grade safety and compliance throughout mission-critical AI workloads.
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