TestSavant AI Testing and Security Reviews & Product Details

Automated Testing of AI Applications: AI-generated test cases and test scripts, autonomous test execution from CI/CD pipelines or schedules, and regression reporting that compares every run with the last, for agentic, RAG, and chatbot applications. TestSavant.AI is an automated testing platform built for AI applications. QA teams use it to generate tests, run them continuously, and track quality across every model, prompt, and application change. Traditional software testing tools are not designed to test probabilistic models or prompt-driven behavior. TestSavant fills that gap with AI test generation, autonomous execution, and regression reporting in a single platform. How TestSavant Works TestSavant analyzes an AI application's description, workflow, and scope, then generates test cases matched to its intended use. A test agent executes those tests against the application through its API, a browser, or the Chrome extension, and evaluates every response against expected behavior. Reports compare each run with previous runs to flag regressions. Tests run on demand, on a schedule, or on every commit and deployment from a CI/CD pipeline. Key Capabilities AI Test Generation from Application Analysis TestSavant analyzes the application's description, workflow, and scope, then generates test cases matched to its intended use. Teams steer generation with natural language instructions, reuse or upload existing test datasets, or generate multi-turn conversation tests. AI-Generated Test Scripts from Recorded Sessions The ts-harness CLI points a browser at a web-based AI application, records the session from a seed prompt, and generates a Playwright test script that replays against the target. Autonomous Test Execution A test agent runs tests in adaptive batches, evaluates each batch, and focuses the next batch on the failures it found. Tests run through the application API, a browser, or the Chrome extension. Self-Maintaining Tests When the interface of a web-based AI application changes, the Chrome extension rediscovers input and response elements on each page load, using an automatic page scan or AI selector detection, so tests keep running without script edits. When application behavior or scope changes, one action regenerates behavior statements and test cases from the updated description. Testing Types Functional testing against expected and prohibited behavior, reference answers, and structured JSON output. Behavioral and conversational quality testing for hallucination, instruction following, tone, clarity, and off-topic responses. Performance tracking of latency and cost on every run. Adversarial robustness testing through AI red teaming. Continuous and Iterative Testing Run tests on demand, on a recurring schedule, or on every commit and deployment from a CI/CD pipeline, as many times a day as the pipeline runs. After a fix, track the issue in Jira, then rerun the same test dataset to confirm the issue is resolved and catch new or related issues. Name each run after what changed, such as a model or prompt version, to compare results side by side. Fits Agile and Phase-Gated Delivery Pass/fail thresholds in the CI/CD pipeline check each sprint build. Scheduled or manual runs cover milestone sign-off in phase-gated releases. Test Reporting and Regression Tracking A failure rate trend covers every historical run, by suite and by policy. Per-run reports include plain-language summaries. Each test case shows the evaluator's reasoning and evidence. Results export to CSV and Excel. Integrations GitHub Actions and any CI/CD system through the Python SDK and CLI, with configurable pass/fail thresholds and exit codes. Jira export turns each test run summary into a Jira issue, either on demand or automatically after every run. REST API. MCP server for AI coding agents such as Claude Code and Cursor. Connects to OpenAI, Anthropic, AWS Bedrock, and Azure OpenAI endpoints, any hosted application or HTTP API, and any web chat interface through the TestSavant.AI Chrome extension. Test Driven Runtime Guardrails Enforce the policies validated in testing in production, with low latency guardrails. Who It's For * QA and SDET teams responsible for testing AI applications before release * Engineering teams shipping AI agents, RAG applications, and chatbots through CI/CD * AI teams iterating on models and prompts who need regression results on every change * AI assurance teams responsible for AI policies TestSavant helps organizations ship AI faster with confidence in quality at every release.