How to implement end-to-end evaluation and observability for AI applications with built-in governance

How to implement end-to-end evaluation and observability for AI applications with built-in governance

This task can be performed using Bifrost

Bifrost is the fastest LLM gateway, with just 11μs overhead at 5,000 RPS, making it 50x faster than LiteLLM.

Best product for this task

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Bifrost

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Bifrost is the fastest, open-source LLM gateway with built-in MCP support, dynamic plugin architecture, and integrated governance. With a clean UI, Bifrost is 40x faster than LiteLLM, and plugs in with Maxim for e2e evals and observability of your AI applications.

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What to expect from an ideal product

  1. Bifrost's integrated governance features automatically track and monitor AI application performance across the entire pipeline, giving you complete visibility into how your models behave in production
  2. The built-in MCP support lets you connect multiple evaluation frameworks directly through the gateway, so you can run continuous assessments without building custom integrations
  3. Dynamic plugin architecture means you can add new monitoring tools and evaluation metrics on the fly, adapting your observability setup as your AI applications grow and change
  4. Integration with Maxim provides real-time evaluation capabilities that work seamlessly with Bifrost's fast gateway performance, letting you catch issues before they impact users
  5. The clean UI consolidates all your evaluation data and observability metrics in one place, making it easy to spot trends, debug problems, and prove your AI systems are working as intended

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