Enhance the safety of AI apps with advanced guardrails
Deploy AI with confidence by implementing robust model guardrails that safeguard data, enhance transparency, and prevent unintended outcomes. Our platform equips you with the tools needed to maintain compliance, ensure reliability, and optimize AI performance at scale.
Key Capabilities
Content safety moderation
Enable mechanisms to detect and mitigate bias and toxicity in model inputs and outputs, with alerts to flag inappropriate requests and responses. Configure a set of custom keywords or phrases that you want blocked, such as competitor references.
Sensitive data leakage
Automatically detect sensitive data sent to agents or through a connected model with robust controls. Detect personally identifiable information (PII) and secrets such as credentials not suitable for usage.
Hallucination detection
Reduce hallucinations with configurable controls to assess the quality and relevance of responses. Implement contextual grounding checks to detect if responses are not grounded in source information.
Adversarial prompt injections
Monitor and block direct and indirect attempts to alter the intended behavior of a model by malicious users. Prevent jailbreak attempts to bypass model restrictions or boundaries.
Cost and performance
Monitor model token costs to detect abnormalities that might be malicious excessive use. Centrally manage model costs and latency to ensure models perform optimally without overloading resources.
Compliance and governance
Ensure model security with full model lifecycle management and controls over usage and access. Gain full visibility over model use with detailed audit logs of requests and responses.
Check out more resources
Video
Highlights from OpenAI DevDay 2024: Key Announcements
October 24, 2024
Explore the latest innovations and announcements from OpenAI DevDay 2024. This video covers new tools, product updates, and insights into the future of AI development shared during the event.
