Braintrust vs Portkey: gateway with evals vs gateway with guardrails

Braintrust and Portkey serve overlapping but distinct AI infrastructure needs: Braintrust emphasizes evaluation, observability, and release control, while Portkey, now underlying Palo Alto Networks’ generally available Prisma AIRS AI Gateway, focuses on request-time routing, governance, and security. Braintrust Gateway, which remains free in beta, supports major providers, custom endpoints, cross-SDK model switching, ordered failover, encrypted response caching, and deep links between production traces, datasets, experiments, automated scoring, and CI/CD release gates, but it does not synchronously block unsafe requests or enforce per-key budgets and quotas. Portkey offers a broader model and tool catalog, richer conditional routing, load balancing, retries, canary deployments, semantic caching, inline input and output guardrails, and policy-based controls such as model restrictions, spending limits, and rate limits. Both platforms provide prompt versioning, tracing, self-hosting options, and enterprise deployment models, although Braintrust’s customer-cloud and self-hosted data planes require Enterprise, whereas Portkey’s MIT-licensed gateway can be independently self-hosted. Braintrust is positioned as more suitable for teams making quality evaluation a formal part of development and production release decisions, while Portkey is better suited to applications requiring sophisticated gateway orchestration and real-time security enforcement; organizations can also combine them by using Portkey in the request path and Braintrust for application-level tracing and evaluation.

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