Safety and security for production AI
Baseten gives enterprises the secure foundation and is developing frontier safety controls to protect sensitive workloads, monitor model behavior, and constrain agent actions.
Enterprise security
Run sensitive AI workloads with controls for your data, your team, and your infrastructure - without sacrificing performance or developer experience
Zero data retention
Serve models with zero retention of inference inputs and outputs, plus encryption in transit and at rest. Protect sensitive customer and proprietary data as models run.
Control access management
Centralize authentication with SSO and manage permissions with role-based access controls. Use service accounts to automate workflows without sharing human credentials.
Deploy with control
Choose a deployment architecture that meets your requirements for workload isolation and data location - from dedicated deployments to inference running inside your own VPC.
Protect data and artifacts
Securely connect your data with native cloud IAM integrations. With BYOK encryption, exercise independent control over access to model weights and payloads.
Constrain network exposure
Enforce isolation and segregation through fine-grained network policies. Control how workloads connect to keep production traffic aligned with your security guidelines.
Simplify security review
Accelerate time to deployment no matter your compliance requirements. Review our certifications, policies, and external audits on the Baseten Trust Center.
Safety beyond the infrastructure
Secure infrastructure is only part of the picture. Baseten is advancing safety across model training, inference, and agent execution - so teams can better understand model behavior and put boundaries around what agents can do.
Understand model behavior
Baseten and Goodfire are working to surface safety signals inside supported open models during inference - helping teams identify risky behavior and decide when to intervene.
Secure agent runtime
Baseten supports OpenShell in its sandbox cloud so teams can apply boundaries around credentials, files, network access, and tools outside the agent’s own code.
Advance safer open models
Base Labs is publishing methods for safer training, monitoring, and evaluation. Baseten connects this research to infrastructure that trains and serves models.
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