AI-Powered API Testing for REST, GraphQL and gRPC

API testing is the module most teams start with, because most systems now expose more behavior through APIs than through a browser UI. NexGen QA's API testing supports REST, GraphQL, and gRPC in one module, with the request-building, chaining, and assertion tooling a manual or AI-assisted tester needs day to day.

Core capabilities

• Request builder supporting method, URL, headers and body — JSON, form-data, raw, or binary.
• Environment variables and request chaining for multi-step workflows, where one response feeds the next request.
• Built-in SSRF protection blocking requests to internal networks.
• Tenant-isolated test collections per organization.
• Response validation with JSON path assertions.
• Authentication handling for Bearer tokens, API keys, OAuth 2.0, and Basic auth.
• Import from Postman, Swagger/OpenAPI, and cURL, so existing collections don't need to be rebuilt.

GraphQL and gRPC specifics

GraphQL testing adds schema introspection and validation, query and mutation testing with variable support, subscription testing for real-time data, and query depth/complexity analysis with N+1 query detection — issues that a REST-shaped testing tool typically can't see because they're specific to how GraphQL resolves nested fields. gRPC support covers the same request/response and assertion model for services that don't expose a REST or GraphQL surface at all.

AI test generation for APIs

You can describe an API test in plain English — for example, "test that creating an order with a valid cart returns a 201 with an order ID, and that the same request without an auth token returns a 401" — and AI test generation converts it into an executable test with assertions and test data. This is the same underlying engine (GPT-4o, Claude, Gemini, DeepSeek, or a custom model you register) used for UI and database test generation elsewhere in the platform.

Security and isolation by default

Two details matter for teams testing APIs that touch production-adjacent infrastructure. First, SSRF protection is built in, not opt-in — requests are blocked from reaching internal networks even if a test is misconfigured to try. Second, test collections are tenant-isolated per organization, so one team's saved requests, environment variables and secrets are not visible to another organization on the same platform.

Authentication and multi-step workflows in practice

A realistic API test suite is rarely a single request — it's a login call, a token extracted from the response, and then several dependent calls that need that token. Environment variables and request chaining exist for exactly this: a value captured from one response (an auth token, a created resource ID) can be referenced in the next request in the chain, so a full workflow — create a resource, fetch it, update it, delete it, confirm the delete — can be expressed as one connected test rather than four disconnected requests a human has to wire together manually each time.

Contract testing for microservices

For teams running multiple services that call each other, Contract/Pact testing runs alongside the core API module: consumer-driven contract definitions, provider verification against those contracts, a contract registry for version management, and breaking-change detection. This catches a class of bug that request-level API testing alone tends to miss — a provider service changing its response shape in a way that's still a valid response, but breaks a consumer that depended on the old shape.

Where API testing fits with the rest of the platform

API tests commonly need to run alongside security scanning (the same endpoint you're functionally testing is also a DAST/SAST target), performance testing (the same endpoint under load), and CI/CD quality gates. Because these are modules in the same platform rather than separate tools, results for the same endpoint correlate in one dashboard instead of three.

Environment management across dev, staging and production

A single collection of API tests usually needs to run against more than one environment — a local or dev API, a staging deployment, and eventually production for smoke checks — each with different base URLs, credentials, and sometimes different expected values. Environment variables handle this by letting the same test collection point at whichever environment is selected for a given run, rather than requiring a separate, duplicated copy of every test per environment.