Modern Enterprise API Testing — Self

Can Total Shift Left run fully on-prem with our own LLM?

Yes. The Enterprise tier supports self-hosted LLM inference via Ollama, LM Studio, and vLLM (or any OpenAI-compatible endpoint). API specifications, prompts, and generated tests stay inside your perimeter — nothing is sent to OpenAI, Anthropic, or any third-party LLM unless you explicitly configure a cloud provider. The deployment is single-tenant, on infrastructure you control.

How is this different from ReadyAPI, Tricentis Tosca, or Parasoft SOAtest?

Those platforms were built before LLMs existed and bolt AI features onto a 20-year-old testing engine. Total Shift Left is AI-native: a multi-provider LLM abstraction (13+ providers including self-hosted), an MCP server for agent integration with Claude and Cursor, and a modern UI. We support the same enterprise needs — on-prem deployment, REST/SOAP/GraphQL, RBAC, audit logs — without the legacy architecture.

Why not just use Postman or Apidog for AI test generation?

Cloud-only AI tools require sending your API specifications and request bodies to third-party LLMs. For BFSI, healthcare, government, and other regulated workloads, that is a non-starter under most security and data-residency policies. Total Shift Left lets you keep specs and prompts inside your perimeter while still getting AI-generated tests.

What enterprise CI/CD integrations are available?

First-party plugins for Jenkins (Java/Maven), GitHub Actions, Azure DevOps (VSTS task), GitLab CI, CircleCI, and Bitbucket Pipelines — six in total. Each integrates the test run lifecycle (trigger, poll, JUnit/JSON artifact), supports quality gates, and is published as a real plugin rather than a generic webhook wrapper. A public REST API is available for any CI system not on this list.

How does identity and access control work?

Built-in RBAC with five roles (Administrator, Contributor, Reviewer, Reader, Environment Manager), per-project assignment, audit logs, and AES-256 encrypted credential storage. SAML 2.0, OIDC, and Azure AD/Entra ID SSO are on the near-term roadmap; until they ship, enterprise customers can integrate via professional services.

Which protocols and specs are supported?

REST, SOAP (with WSDL parsing), and GraphQL — production-ready. OpenAPI 3.0/3.1 and Swagger 2.0 import. gRPC and Postman collection import are on the roadmap. The platform auto-discovers endpoints, parses schemas, and generates tests for every operation.

What does deployment look like for a regulated enterprise?

Self-hosted on infrastructure you control (Linux or Windows VMs, with Nginx and MongoDB). Multi-tenant SaaS is also available for non-regulated workloads. Containerized (Docker / Kubernetes / Helm) install paths are on the roadmap; today, deployment is via documented installation scripts. Implementation timelines are scoped per environment — talk to our architect on the demo call.

How does Total Shift Left integrate with AI agents?

A native MCP (Model Context Protocol) server exposes six tools — generateTests, enrichTest, explainCoverage, generateForGaps, analyzeEndpoint, validateTests — plus four resource types over stdio transport. This means Claude, Cursor, and any MCP-compatible agent can drive test generation and coverage analysis directly. Available on Professional and Enterprise tiers.