How do their growth rates compare?

QA.tech has a month-over-month growth rate of -4.4%; Cekura (formerly Vocera) has 0%.

How does pricing compare?

QA.tech: Paid, Contact for Pricing. Enterprise-style, contact-for-pricing model: the site offers a free getting-started path and a demo booking rather than public per-seat numbers, so exact costs depend on team size, coverage scope and mobile testing needs. Cekura (formerly Vocera): Contact for Pricing. Pricing is sold as a free trial followed by paid plans, with enterprise and custom quotes available by booking a demo. Exact plan amounts are not published on the homepage.

What are alternatives to QA.tech and Cekura (formerly Vocera)?

Other tools in related categories include KaneAI, Qase, Katalon, Mindgard, Future AGI.

QA.tech vs Cekura (formerly Vocera) — Traffic (30.55K vs 0), Pricing & Verdict

Open AI Tools

QA.tech vs Cekura (formerly Vocera) — Traffic (30.55K vs 0), Pricing & Verdict | Open AI Tools

Side-by-Side Traffic & Specification Matrix

Dimension / Metric	QA.tech	Cekura (formerly Vocera)
Official Domain	qa.tech	vocera.ai
Pricing Model	Paid, Contact for Pricing	Contact for Pricing
Monthly Visits	30.55K (30,550)	0 (0)
MoM Traffic Delta	-1.42K (-4.4%)	0 (0%)
Primary Market & Share	🇸🇪 Sweden (24.4%)	🌐 Global (—)
Direct Visits / mo	21.23K	0
User Rating	4.3	4.5
Supported Platforms	Website	Website

QA.tech

Autonomous AI QA agents that verify your web and mobile app on every pull request

Plain-language test authoring

Describe a journey or rule in chat and the agent turns it into durable test cases that survive refactors and redesigns.

PR-level verification

Every pull request gets a dynamic exploratory pass with preview environments, failure breakdowns, screenshots, console and network logs.

Web and native mobile

Agents target real browsers and native iOS and Android apps, so coverage reaches beyond the web front end.

CI, Git and issue-tracker integrations

Findings flow into Jira and Linear, and agents can be queried over MCP by other coding agents.

Strengths & Pros

+Agents test visually without selectors, so suites survive redesigns and framework migrations
+Runs automatically on every pull request with preview environments
+Plain-English test authoring is accessible to non-engineers
+Rich failure evidence — screenshots, logs, network data and agent reasoning