--- source_url: "https://www.swarmcheckai.com/?utm_source=openai" title: Swarmcheck — AI QA agents that test your real app mirrored_at: 2026-08-09T01:08:08.035Z host: www.swarmcheckai.com cited_in_42a: true mirror_canonical: "https://index.42a.ai/www.swarmcheckai.com/index__q__utm_source_openai" --- > **Original source:** https://www.swarmcheckai.com/?utm_source=openai \[ QA FOR PRODUCTS WITH AI INSIDE \] ## Test the whole product. Including the AI parts. Every team uses AI to build faster. Almost none of them have a way to test what they shipped. Swarmcheck checks your UI flows with a persona swarm and validates your AI features with semantic assertions — hallucinations, prompt injection, response-quality regressions — on every PR. "Everyone else uses AI to run your tests. We test the AI inside your product. That's a different problem." The missing link in QA Traditional QA can’t check if your AI works. Swarmcheck is built for product teams—not just LLM engineers—so you catch AI failures before users do. The assertion problem ## Six ways AI features fail. Five of them your QA tool can't see. Traditional tests check exact (deterministic) outputs. AI features return valid but varied results each run—only Swarmcheck catches all six failure modes. Failure mode What it looks like Traditional QA? Swarmcheck? Hallucination Your AI support chat invents a refund policy that doesn't exist. ❌ No ✅ Yes Prompt injection A user manipulates your assistant into leaking the system prompt — affects 73% of production AI deployments. ❌ No ✅ Yes Non-determinism regression After a model update, response quality drops 15% but no test fails. ❌ No ✅ Yes Tool call failure An AI agent calls the wrong API or passes bad parameters. ❌ No ✅ Yes Boundary violation The AI happily answers questions outside its intended scope. ❌ No ✅ Yes UI regression on AI surfaces The chatbot loads but streams blank text on Safari. ✅ Yes ✅ Yes Two modules, one product ## The familiar entry point. The wedge nobody else has. Module 1 · Swarm Tests (End to End Testing) ### The whole web product, exercised by a persona swarm. Flows, forms, payments, navigation — the deterministic surface. Parallel persona agents drive the live app the way different users would. Familiar territory, sharper coverage. This is the door teams walk in through. Module 2 · AI Assertions Launching soon ### The AI features inside the product, tested the way AI needs to be tested. Semantic assertions, hallucination checks, prompt injection probes, LLM-as-judge quality regressions, tool-call validation. The wedge nobody else owns — and the reason teams stay. AI Assertions ## The assertions traditional QA can't write. 0 1 ### Semantic assertions, not string matching Score outputs against a plain-English rubric with an LLM judge. Pass when the meaning is right, even if the wording shifts. Judges agree with humans up to 85% — higher than humans agree with each other. What it checks - Intent and correctness against your rubric, not exact phrasing. - Tolerance for wording/style variation when meaning stays correct. - Confidence trend for pass/fail decisions over repeated runs. 0 2 ### Hallucination detection Probe your AI feature with questions whose answers are known — pulled from your knowledge base or from facts you define. Get a hallucination rate per run, tracked across releases. What it checks - Known-answer prompts sourced from your approved facts. - Per-run hallucination rate with release-over-release deltas. - Exact failing prompts and model responses for triage. 0 3 ### Prompt injection probing Every PR fires an adversarial suite at your AI surface — the OWASP #1 LLM vulnerability. Pass means the guardrails held. Fail blocks the merge. What it checks - System prompt leakage attempts and role escalation probes. - Bypass attempts against policy, tone, and safety guardrails. - Merge-blocking verdict when exploit patterns succeed. 0 4 ### Response quality regression (LLM-as-judge in CI) Update a system prompt, swap a model, edit your RAG corpus — Swarmcheck re-scores the benchmark suite and flags every regression against the previous baseline. What it checks - Quality score diff versus previous baseline on each PR. - Regression alerts by scenario, persona, and environment. - Historical score trend to catch slow quality drift. 0 5 ### Tool call validation for AI agents If your product embeds an agent that calls tools, Swarmcheck validates behaviour in a sandbox: right tool, valid params, terminates cleanly, no leaked context. What it checks - Correct tool selection for the user intent in context. - Argument schema validity and safe parameter boundaries. - Clean agent termination with no sensitive context leakage. What it does ## Everything you need to ship without breaking things. ### Real-app testing Agents drive a live browser the way a user would — clicking, typing, waiting, scrolling — so you catch real bugs, not just unit failures. ### Plain-English tests Describe what you want checked in a sentence. No selectors, no waits, no flaky scripts to babysit. ### Auth, OTPs, OAuth Agents log in, complete OAuth handshakes, and receive one-time codes through dedicated inboxes. Secrets stay encrypted at rest. ### Wired into your PRs Connect the GitHub App and every pull request gets its own check, complete with a verdict and links to the evidence. ### Web and mobile Same product, same tests, three platforms. Web, iOS, and Android run from a single project. ### Production monitoring Schedule recurring runs against prod and get pinged the moment a critical flow breaks for real users. How it works ## From a fresh project to AI checks on every PR in four steps. 01 ### Point us at your app Drop in a URL or upload a build. Tell us which surfaces use AI — chat, search, agent, generative blocks. 02 ### Describe what 'good' looks like Plain-English rubrics for AI outputs. Plain-English flows for everything else. No selectors, no eval scaffolding to maintain. 03 ### Wire it into every PR Swarm Tests (End to End Tests) and AI Assertions run on each pull request, on every preview deploy, and on a schedule against production. 04 ### Read a verdict you can trust Pass / fail, hallucination rate, quality delta, recordings, and the exact prompt or step that broke. Posted to your PR and Slack. Built for your stack ## Drops in next to whatever you already ship with. ### PR checks for the AI parts too Hallucination rate, quality delta, prompt-injection results — posted on every pull request, with links to the failing prompts and recordings. ### Lives where your team already does Slack, Linear, Jira, GitHub Issues, PagerDuty. Send AI regressions to the inbox the on-call actually reads. ### Run it in your own VPC Self-hosted runners on AWS, GCP, or Azure so your prompts and AI outputs never leave your perimeter. SSO and audit logs included on enterprise. Integrations ## Integrates with your stack. Connect Swarmcheck to the tools your team already uses to plan, build, and ship. Claude Cursor Playwright Gemini Jira Confluence Azure DevOps Slack GitHub Notion Monday.com Many more... Security & compliance ## Built for enterprise security. Industry-standard certifications. Your data stays protected. Coming Soon SOC 2 Type II Certified Independently audited security, availability, and confidentiality controls, verified annually. Coming Soon ISO 27001 2022 Edition International standard for information security management systems, independently certified annually. Coming Soon GDPR EU Compliant Full EU data protection compliance with DPAs available. No data retained after job completion. Who this is for ## If your product has AI in it, this is the QA tool you've been missing. As of 2026, 60% of YC batches are AI companies. Every one of them ships AI into a web product. None of them have a purpose-built tool for testing it. That's the beachhead. Primary ### SaaS teams shipping AI features—chatbots, AI search, embedded agents—or needing better UI and AI test coverage. "We don't know how to test the AI chat we just shipped, and our traditional flows are hard to keep covered." AI Assertions + full E2E flow coverage Secondary ### Vibe-coded and AI-generated codebases moving at speed. "We ship fast but have zero test coverage." Swarm Tests as the familiar entry point Tertiary ### Any team on Vercel-style preview deploys. Standard regression QA without the scripting overhead. Swarm Tests as the commodity layer Where teams use it ## Wherever bugs slip through today. 20× Faster than scripted E2E suites\* 4 min Median time from PR open to verdict 0 Selectors written, ever 100% Of runs ship a video and a trace \* Figures based on internal benchmarking; audited benchmarks to be published. \[07\] What teams say ## Quotes we'd love to put real names on. FAQ ## Need answers? ## Ship AI features with proof they work — not hope. See Swarmcheck running AI Assertions against your own product in a 20-minute call. No slideware. [Get a demo](https://www.swarmcheckai.com/contact)