Eval directory
Evals for Portkey
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Portkey AI products.
About Portkey
Portkey is an AI gateway for production LLM apps — a unified, OpenAI-compatible API across 200+ models with provider routing and fallbacks, semantic and simple caching, input/output guardrails (PII redaction, prompt-injection, content moderation), request-level observability and traces, a versioned prompt library, virtual keys with per-key budgets and rate limits, and workspace RBAC + audit logs.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
8/8 packs
Scoring metrics
0/8 packs
Judge rubrics
8/8 packs
Use-case maps
0/8 packs
Pack context
8/8 packs
Available eval packs for Portkey
8 packs ready to run.
Caching Simple And Semantic
Evaluates Portkey's Simple & Semantic across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Configs And Virtual Keys
Evaluates Portkey's Configs & Virtual Keys across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Guardrails Input And Output
Evaluates Portkey's Input & Output Guards across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Observability Logs And Traces
Evaluates Portkey's Observability, Logs & Traces across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Prompt Library And Versioning
Evaluates Portkey's Prompt Library & Versioning across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Provider Routing And Fallbacks
Evaluates Portkey's Provider Routing & Fallbacks across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Safety Rbac And Governance
Evaluates Portkey's Safety, RBAC & Governance across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Unified Api And Gateway Proxy
Evaluates Portkey's Unified API & Gateway Proxy across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Gateway eval coverage.
Why eval Portkey AI
Portkey's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for Portkey measures four dimensions teams care about most when deploying ai platform agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against Portkey's public product surface and runnable in Corsac with your own data.