qAPI
Tests whether your APIs actually work — including the AI-powered ones — without needing someone on the team who can write test-automation code, since it's built to be set up by clicking rather than scripting.
🔗 Visit qAPI
Description
Testing an API properly usually means someone writing and maintaining test scripts, which is a skill (and time cost) plenty of teams don't have to spare, especially smaller ones without dedicated QA engineers. qAPI's pitch is codeless test creation: you build test cases through a visual interface instead of writing automation code, covering REST, GraphQL, SOAP, and gRPC.
Beyond the standard schema validation, latency checks, and load/performance testing you'd expect from an API testing tool, qAPI's more unusual feature is built-in evaluation for LLM and RAG systems — testing AI-powered endpoints for things like hallucination rate, not just correct status codes. It includes an AI assistant ("Nova") that suggests test cases and assertions automatically, supports importing existing test suites from Swagger, Postman, or OpenAPI specs, and runs entirely in the cloud with no local setup — claimed under an hour to get started. It's a distinct product line inside the broader Qyrus QA suite rather than a side feature, though pricing details beyond "free trial available" aren't published on the site.
💬 Our review
The short version: if your team is testing APIs that include LLM or RAG components alongside normal REST endpoints, qAPI is one of the few tools that treats AI-output evaluation as a first-class citizen rather than an afterthought, which is a real gap in most established API testing tools.
For plain API testing without the AI angle, Postman remains the dominant, more battle-tested choice with a far larger ecosystem, integrations, and community — qAPI is competing in a crowded space where the incumbent has enormous inertia. qAPI's differentiation is genuinely narrow: codeless setup plus AI/LLM evaluation bundled with standard REST/GraphQL testing. If you don't test AI-powered endpoints, that differentiator disappears and Postman or Insomnia will likely serve you just as well with more community support. Worth evaluating specifically if LLM/RAG testing is part of your API surface; otherwise the switching cost from an established tool probably isn't justified yet.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Paliers tarifaires non publiés publiquement, essai gratuit disponible
Pros
Tests codeless, accessibles sans compétence en scripting d'automatisation
Évaluation intégrée des systèmes LLM/RAG (taux d'hallucination), rare chez les concurrents
Assistant IA (Nova) suggérant tests et assertions automatiquement
Import direct depuis Swagger, Postman, OpenAPI
Cons
Grille tarifaire non transparente publiquement
Écosystème et communauté bien plus restreints que Postman
Positionnement concurrentiel faible sur le test API classique (marché dominé par Postman)
Aucun déploiement on-premise/self-hosted mentionné