# Ito > Ito runs QA testing by executing your code in a real browser. Unlike static analyzers, Ito catches behavioral and runtime bugs that only appear when code actually runs. ## Key Pages - [For QA teams](https://www.ito.ai/for-qa-teams.md) - [Sandboxes for Coding & Security Agents](https://www.ito.ai/features/sandboxes-for-coding-and-security-agents.md) - [Containerized Test Execution](https://www.ito.ai/features/containerized-test-execution.md) - [Pricing](https://www.ito.ai/pricing.md) - [Why Ito](https://www.ito.ai/why-we-built-ito.md) - [Security](https://www.ito.ai/security.md) - [Self-healing Codebase](https://www.ito.ai/features/self-healing-codebase.md) - [Contact](https://www.ito.ai/contact.md) - [Targeted Test Plans](https://www.ito.ai/features/targeted-test-plans.md) - [Evidence Rich Results](https://www.ito.ai/features/evidence-rich-results.md) - [Smoke Testing](https://www.ito.ai/features/smoke-testing.md) - [Product Demo Videos](https://www.ito.ai/features/product-demo-videos.md) - [For engineering teams ](https://www.ito.ai/for-engineering-teams.md) - [Home](https://www.ito.ai/) - [Bug Bashes](https://www.ito.ai/features/bug-bashes.md) - [The Test Tax](https://www.ito.ai/test-tax.md) ## Blog Posts - [Bug Catch of the Week: How a Failed Database Swap Could Delete Your Only Copy](https://www.ito.ai/blog/failed-database-file-replacement-data-loss.md): DoltLite's replacement flow could delete the old database before the new copy was safe. Here's how runtime testing exposed the failure path before release. - [How to Build Quality Into Your Software Factory](https://www.ito.ai/blog/how-to-build-quality-into-your-software-factory.md): Software factories need speed & quality. Ship fewer bugs by testing in layers; fast tests first, then deeper validation - [The AI Model Plateau: Why Your Infrastructure Matters More Than the Next Release](https://www.ito.ai/blog/ai-model-plateau-why-infrastructure-matters-more-next-release.md): AI model routing and evaluation now decide your production results. Learn how companies are adapting to make the most of the highly competitive LLM landscape. - [Why AI Code Review Needs to Read Your Code and Run It](https://www.ito.ai/blog/ai-code-review-read-your-code-run-it.md): A practical guide to static and runtime analysis in AI code review, including what each approach catches, where it falls short, and why teams use both. - [What Happened When DoltHub Ran Ito on 43 Pull Requests](https://www.ito.ai/blog/what-happened-dolthub-ran-ito-43-pull-requests.md): DoltHub reported a 2:1 fixed-to-dismissed ratio for Ito bug findings, and surfaced pre-existing issues in 26 of 43 tested PRs over six weeks. - [MTTR is the Wrong Metric for AI-Era Engineering Teams](https://www.ito.ai/blog/mttr-wrong-metric-ai-engineering-teams.md): AI tools produce 41% more bugs and 98% more pull requests. MTTR can't keep up. Here's how MTTF shifts your team from incident response to prevention. - [Your fastest model is probably not your fastest model](https://www.ito.ai/blog/tokens-per-second-measures-emission-not-work.md): Tokens per second measures how fast a model emits, not how fast it finishes. Our 13-model probe shows the gap that flips both the speed + cost leaderboards. - [Moo: Giving Your Agents the Runtime Isolation git worktrees Need](https://www.ito.ai/blog/moo-worktree-isolated-environments.md): git worktree isolates your files. Moo isolates the database, ports, and services, saved per commit. Together, they give your agents fully isolated machines. Learn how to use Moo, the benefits, and why your agents need it. - [What we learned after moving 100B tokens/week to open-weight models](https://www.ito.ai/blog/measuring-100b-tokens-week-open-weight-models.md): Ito moved production QA agents from GPT-5.3-codex to open-weights. Here's what we saved, why inference providers matter as much as models, and what to check. - [Elevate Software Testing: 10 Best Practices for 2026](https://www.ito.ai/blog/software-testing-best-practices.md): Boost your Test. Learn 10 software testing best practices for 2026, covering pre-merge, scriptless, and agentic methods for managers. - [Static Analysis Misses Bugs That Reach Production](https://www.ito.ai/blog/static-analysis-misses-bugs-that-reach-production.md): Agents can stare at code all day long, but they will not find all the issues because they are probabilistic unit tests. You need to actually run your application to get runtime evidence and proof that things behave as your organization expects them to for full integration and end-to-end tests. - [Your AI-scaled engineering org needs big-org processes](https://www.ito.ai/blog/your-ai-scaled-engineering-org-needs-big-org-processes.md): When developers are 3–5x more productive with AI, your org is effectively that much bigger. Your operations need to follow suit. - [What is agentic QA? The complete guide](https://www.ito.ai/blog/what-is-agentic-qa-the-complete-guide.md): How autonomous AI agents are replacing brittle E2E scripts with behavioral testing that actually validates the user experience. - [AI-Driven Testing: Why Your QA Still Runs Like It's 2015](https://www.ito.ai/blog/ai-driven-testing-why-your-qa-still-runs-like-its-2015.md): Discover how AI-driven testing replaces brittle QA automation, cuts bottlenecks, and helps modern teams ship faster with more confidence. ## Comparison Pages - [Ito vs Qodo: Generating Tests vs Running the App](https://www.ito.ai/compare/ito-vs-qodo.md) - [Ito vs Cursor Bugbot (2026): Reviewing the Code You Just Generated](https://www.ito.ai/compare/ito-vs-cursor-bugbot.md) - [Greptile Alternatives: Ito vs Greptile Compared ](https://www.ito.ai/compare/ito-vs-greptile.md) - [Ito vs CodeRabbit: Reading the Diff vs Running the Code](https://www.ito.ai/compare/ito-vs-coderabbit.md) - [Ito vs Claude Code Review: How Each Reviews a PR](https://www.ito.ai/compare/ito-vs-claude-code-review.md) - [Ito vs Mabl](https://www.ito.ai/compare/ito-vs-mabl.md) ## References - [Sitemap](https://www.ito.ai/sitemap.xml) - [Full Content](https://www.ito.ai/llms-full.txt) - [Blog RSS](https://www.ito.ai/rss.xml) - [Docs](https://www.ito.ai/docs)