Problem solved

Organizations deploying multiple AI models face challenges in routing, security, monitoring, and quality evaluation. Respan Gateway provides a unified entry point that streamlines model serving, offers built-in observability to track performance and usage, and includes evaluation tools to assess model outputs, reducing operational complexity.

Use cases

• Centralized routing of API requests to different AI models based on request content, user, or version.
• Monitoring model latency, error rates, and throughput through built-in dashboards.
• Running automated evaluations on model predictions to detect drift or degradation.
• Implementing rate limiting and authentication for AI APIs.
• A/B testing multiple model versions to compare performance before full rollout.
• Logging all inference requests and responses for compliance and debugging.

Audience

• Developers
• ML Engineers
• Data Scientists

Pros

• Unified gateway for all AI models simplifies infrastructure.
• Built-in observability reduces need for separate monitoring tools.
• Integrated evaluation capabilities enable continuous quality checks.
• Potential to support multiple model types and providers.
• Centralized security and access control.

Cons

• Pricing and licensing unclear, may be cost-prohibitive for small teams.
• May have limited customization compared to open-source alternatives.
• Vendor lock-in risk if deeply integrated with specific cloud provider.