Portkey

When an application makes calls to language models whether OpenAI, Anthropic, Google, Mistral, or any of dozens of other providers all traffic routes through Portkey, which adds a layer of capabilities that would otherwise require significant custom engineering to build: automatic failover to backup providers when a primary model is unavailable, load balancing across multiple API keys or providers, semantic caching that serves repeated similar queries from cache rather than making redundant model calls, and comprehensive logging of every request and response for debugging and cost analysis.

The platform's observability layer captures granular data on every LLM call: model used, token counts, latency, cost, success rate, and the full request-response payload indexed and searchable for debugging specific production failures or analyzing performance patterns over time.

This visibility is essential for teams running AI features in production where the combination of non-deterministic model responses, variable latency, and per-token pricing makes monitoring and cost management meaningfully more complex than traditional API integrations.

Teams use Portkey's analytics to identify which prompts are most expensive, where latency spikes originate, and how changes to model or prompt configuration affect reliability and quality.

Portkey integrates via OpenAI-compatible SDK, meaning teams can adopt it by changing a single line of configuration in their existing AI code rather than rewriting their integration layer.

It also supports prompt management storing, versioning, and deploying prompts through Portkey's interface so that prompt changes can be made without code deployments.

For AI engineering teams responsible for maintaining reliable, cost-efficient, and observable AI features in production applications, Portkey eliminates the need to build a custom AI infrastructure layer, reducing the operational overhead of running AI in production while improving the reliability and observability of every model interaction.