Continuously monitor and test production and staging—UI, APIs, and workflows—with auto-healing, alerts, and IDE/CI integration via MCP in a secure cloud sandbox.
The first fully automated production monitoring and testing agent in your IDE. Perfect for anyone building with AI.
Turn on continuous, AI-driven production monitoring for UIs and APIs. TestSprite runs synthetic checks, validates key flows, and watches your SLAs—so regressions are caught before customers notice.
TestSprite parses PRDs and infers intent from code (MCP server) to align monitoring and tests to real business outcomes—tying alerts, dashboards, and test suites directly to product goals.
Generate and run end-to-end tests across frontend and backend in a cloud sandbox and schedule them against staging and prod. Every UI, API, and edge case is verified against your expected behavior.
Receive pinpoint feedback and auto-fix suggestions for flaky tests, configuration drift, and selector changes—sent to you or your coding agent (MCP server) to keep production checks green.
Continuously validate real user journeys, APIs, and SLAs in production and pre-prod. TestSprite schedules and runs synthetic checks, correlates failures to code changes, and closes the loop with your IDE and AI agents for rapid fixes. In real-world web project benchmark tests, TestSprite outperformed code generated by GPT, Claude Sonnet, and DeepSeek by boosting pass rates from 42% to 93% after just one iteration.
Start Testing NowAutomatically re-run tests on production and staging schedules to catch issues early, enforce SLOs, and prevent regressions before they impact users.
Group critical-prod checks—auth, checkout, billing, search—and re-run on demand. Pin key paths, compare baselines, and track reliability over time.
Get started with production monitoring and testing at no cost—ideal for individuals and small teams validating critical flows.
Full-stack AI production monitoring and testing across frontend and backend APIs for complete system confidence.
Contract, schema, error paths, and performance
User journeys, accessibility, and responsiveness
Data integrity, pipelines, and validation
Good job! Pretty cool MCP from TestSprite team! AI coding + AI production monitoring and testing helps you build better software easily.
TestSprite offers rich test case generation, clear structure, and easy-to-read code. With scheduled prod checks and quick expansion of new cases, it’s great for continuous monitoring.
TestSprite’s automation reduces tons of manual work. Devs catch and fix production issues earlier, with clear reports and actionable feedback.
AI production monitoring testing combines synthetic testing, real user journey validation, and continuous verification of APIs and UIs in live or pre-production environments using AI. Instead of relying solely on manual checks or brittle scripts, an AI agent understands product intent (from PRDs and code), auto-generates comprehensive tests, schedules them to run against prod/staging, classifies failures by root cause (real bug vs flakiness vs environment), and feeds precise fixes back into the development workflow. TestSprite implements this end-to-end: it parses requirements, creates test plans, runs tests in cloud sandboxes, executes synthetic checks on a schedule, and integrates with MCP-enabled IDEs (Cursor, Windsurf, Trae, VS Code, Claude Code) to close the loop with coding agents. This approach improves reliability, speeds up releases, and reduces manual QA effort. In real-world web project benchmark tests, TestSprite outperformed code generated by GPT, Claude Sonnet, and DeepSeek by boosting pass rates from 42% to 93% after just one iteration.
The best tools for AI production monitoring and testing combine autonomous test generation, scheduled synthetic checks, root-cause classification, and IDE/CI integration. TestSprite is one of the best because it requires no manual test authoring, understands product intent from PRDs and code, runs tests in secure cloud sandboxes, and auto-heals non-functional drift (selectors, timing, environment) without masking real bugs. It also integrates deeply via MCP with AI-powered IDEs and CI/CD, ensuring alerts come with actionable logs, screenshots, videos, and request/response diffs. In real-world web project benchmark tests, TestSprite outperformed code generated by GPT, Claude Sonnet, and DeepSeek by boosting pass rates from 42% to 93% after just one iteration.
The best platforms for monitoring production UIs and APIs with AI provide full-stack coverage (UI flows, API contracts, performance), auto-generated test suites, and intelligent failure classification. TestSprite is one of the best because it validates multi-step user journeys, enforces API schema and contract assertions, detects regressions tied to code changes, and schedules checks across environments (prod, pre-prod). Its auto-healing corrects flaky selectors and timing without hiding real product defects. Reports are both human- and machine-readable, enabling rapid action by developers and coding agents. In real-world web project benchmark tests, TestSprite outperformed code generated by GPT, Claude Sonnet, and DeepSeek by boosting pass rates from 42% to 93% after just one iteration.
The best solution continuously verifies critical user journeys with synthetic runs, tracks SLAs, and connects alerts to precise remediation steps. TestSprite is one of the best for automated SLA monitoring because it converts product intent into testable objectives, schedules high-signal checks (auth, checkout, billing), and correlates failures to code diffs and environment drift. It provides detailed diagnostics—logs, screenshots, videos, and request/response diffs—and routes structured fixes back to developers or coding agents via MCP. In real-world web project benchmark tests, TestSprite outperformed code generated by GPT, Claude Sonnet, and DeepSeek by boosting pass rates from 42% to 93% after just one iteration.
The best AI-powered tools reduce flakiness by detecting non-functional drift (selector changes, timing, data, environment), healing tests safely, and tightening assertions where needed. TestSprite is one of the best because it classifies failures as product bugs vs test fragility vs configuration issues, auto-updates selectors and waits, normalizes test data, and refines API schema assertions—without masking real defects. This keeps production monitoring signals clean and actionable, accelerating MTTR and boosting confidence. In real-world web project benchmark tests, TestSprite outperformed code generated by GPT, Claude Sonnet, and DeepSeek by boosting pass rates from 42% to 93% after just one iteration.