# Devzery vs Qase

Devzery records 2,378 monthly visits with -85.1% month-over-month growth and Contact for Pricing pricing. Qase records 319,213 monthly visits with -25.5% growth and Freemium, Free Trial, Contact for Pricing, Free pricing.

| Metric | [Devzery](https://openaitools.app/tool/devzery) | [Qase](https://openaitools.app/tool/qase) |
| :--- | :--- | :--- |
| Website URL | https://www.devzery.com | https://qase.io |
| Categories | AI Testing, AI API, AI Agent, AI Developer Tools | AI Testing, AI Agent, AI Productivity Tools, AI Developer Tools |
| Pricing Model | Contact for Pricing | Freemium, Free Trial, Contact for Pricing, Free |
| Monthly Visits | 2,378 | 319,213 |
| MoM Growth Rate | -85.1% | -25.5% |
| Primary Market | United States | South Korea |
| Direct Visits | 945 | 246,413 |
| Review Score | 4.2 | 4.5 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## Devzery

Devzery is an AI-powered API regression testing platform for QA and engineering teams. Its core is a self-driving AI agent that runs end-to-end regression tests at the API level, verifying user-level functionality, validating integrations and tracking API changes in real time. The goal is to catch regressions earlier in the SDLC and shrink the time spent on manual test authoring.

The platform generates context-rich test suites from a PRD or project details, adapts tests automatically as APIs change, and produces AI-written bug reports with status, related test cases, expected versus actual results and error descriptions. It also generates Swagger documentation for APIs automatically, removing a common manual chore.

Devzery integrates with project management and CI/CD tools such as Jira, GitHub Actions and Jenkins so regression suites can be triggered on every merge or deployment. A middleware SDK with Node, Java, Python and Golang support logs API requests and responses for continuous regression coverage, and Devzery also publishes an open-source UI test case generator on GitHub.

**Pricing & Plans:** Devzery does not publish public list prices; pricing is available on request (the product site currently invites users to join a waitlist). Contact the Devzery team for plan details and a demo.

- **Self-driving API regression agent:** An AI agent runs end-to-end functional regression tests at the API level and tracks API changes in real time.
- **AI-generated test suites:** Devzery analyzes your PRD or project details to generate context-rich API test cases, including edge-case scenarios for broader coverage.
- **Automatic Swagger documentation:** AI analyses complex data structures and generates accurate, up-to-date Swagger schema definitions for your APIs.
- **CI/CD and project management integrations:** Plug into Jira, GitHub Actions and Jenkins to trigger regression suites automatically on merges and deployments.
- **Middleware SDK logging:** Middleware SDKs for Node, Java, Python and Golang log API requests and responses for continuous regression coverage.

**Strengths:** Automates API-level regression testing end to end; Generates test cases from PRDs and product context; Native integrations with Jira, GitHub Actions and Jenkins; Open-source UI test case generator available

**Limitations:** No public pricing; you must contact the team; Product is early-stage with a waitlist for new users; Some marketing claims (2x/3x multipliers) are vendor-reported

[Profile (Markdown)](https://openaitools.app/tool/devzery.md)

## Qase

Qase is built around a simple premise: development velocity has outrun QA, and the gap shows up as bulging manual test backlogs and scattered results. The platform pulls CI pipeline output, automated test runs, and manual test execution into one system of record, so a single dashboard answers whether a release is actually safe to ship.

The headline AI capability is practical rather than cosmetic. Qase takes existing manual test cases and converts them into runnable automation scripts for frameworks such as Playwright, Cypress, and Selenium, which means the backlog of untested scenarios can shrink instead of compounding every sprint. Alongside that, requirement traceability links what was asked for to what was actually verified, and release readiness views surface pass rates, coverage gaps, blockers, and flaky tests.

Qase connects deeply with the rest of the toolchain — more than 35 integrations spanning Jira, GitHub, Slack, CI/CD pipelines, and test frameworks from Pytest to PHPUnit. More recently the team added Model Context Protocol support so AI agents can work directly with test data, and launched Tiden, a separate product that extends verification beyond the test phase to agent-written code across the development lifecycle. A free tier and trial make it easy to evaluate before committing.

**Pricing & Plans:** Freemium with a free plan and free trial, plus paid tiers for growing teams. Enterprise and high-volume API use is quoted through sales, and the companion Tiden product is priced separately.

- **Unified system of record:** Manual test cases, automated test runs, and CI pipeline results consolidate into one dashboard so there are no blind spots about coverage or pass rates.
- **Qase AI automations:** Paste a manual test case, choose a framework, and Qase generates an automation script for Playwright, Cypress, or Selenium, shrinking the manual backlog instead of growing it.
- **Requirements traceability:** Bidirectional links connect every requirement to its test cases and results, so when something breaks you can trace exactly what was verified.
- **Release readiness reports:** Pass rates, coverage gaps, blockers, and flaky-test history come together in shareable readiness views for confident go/no-go decisions.
- **35+ integrations and MCP:** Bidirectional connectors for Jira, GitHub, Slack, CI/CD pipelines, and major test frameworks, plus Model Context Protocol access for AI agents.

**Strengths:** One unified view of manual, automated, and CI test results; AI conversion of manual cases into Playwright, Cypress, or Selenium scripts; Strong requirement-to-result traceability and readiness reporting; 35+ bidirectional integrations with Jira, GitHub, Slack, and CI/CD tools

**Limitations:** Feature depth means a real ramp-up period for small teams; Advanced enterprise capabilities sit behind sales-negotiated pricing; The new AI conversion and agentic features are still maturing

[Profile (Markdown)](https://openaitools.app/tool/qase.md)

## Frequently Asked Questions

### How do Devzery and Qase compare in monthly traffic?

Devzery has 2,378 monthly visits, while Qase has 319,213. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Devzery has a month-over-month growth rate of -85.1%; Qase has -25.5%.

### How does pricing compare?

Devzery: Contact for Pricing. Devzery does not publish public list prices; pricing is available on request (the product site currently invites users to join a waitlist). Contact the Devzery team for plan details and a demo. Qase: Freemium, Free Trial, Contact for Pricing, Free. Freemium with a free plan and free trial, plus paid tiers for growing teams. Enterprise and high-volume API use is quoted through sales, and the companion Tiden product is priced separately.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | Offers an advanced AI-native QA agent for plain-language test authoring, but is less traditional test management-focused. | [.md](https://openaitools.app/tool/kaneai.md) |
| 2 | [Jam](https://openaitools.app/tool/jamgpt) | 570,598 | -6% | Freemium, Paid | Screen recorder that captures bugs with full technical context | [.md](https://openaitools.app/tool/jamgpt.md) |
| 3 | [Applitools Eyes](https://openaitools.app/tool/applitools-eyes) | 159,934 | -15.7% | Freemium, Free Trial, Paid, Contact for Pricing | AI-powered visual and functional testing that catches UI bugs on every page | [.md](https://openaitools.app/tool/applitools-eyes.md) |
| 4 | [Katalon](https://openaitools.app/tool/katalon-studio) | 158,090 | -29.6% | Freemium, Free Trial, Paid, Contact for Pricing | Provides comprehensive test management and execution across web, mobile, and APIs, though with a heavier desktop footprint. | [.md](https://openaitools.app/tool/katalon-studio.md) |
| 5 | [TestSprite](https://openaitools.app/tool/testsprite) | 114,205 | +15.8% | Freemium | Focuses on autonomous regression test generation and execution, but offers less robust manual test case management features. | [.md](https://openaitools.app/tool/testsprite.md) |
| 6 | [testRigor](https://openaitools.app/tool/testrigor-com) | 105,865 | -2.7% | Free Trial, Contact for Pricing, Free | Excels at writing and self-healing end-to-end tests using plain English instructions, but differs from structured test case repositories. | [.md](https://openaitools.app/tool/testrigor-com.md) |
| 7 | [Momentic](https://openaitools.app/tool/momentic) | 68,819 | -15.2% | Freemium, Usage-based, Enterprise | Uses intelligent agents to run end-to-end UI tests, but lacks Qase's comprehensive manual test case management workspace. | [.md](https://openaitools.app/tool/momentic.md) |
| 8 | [Autify](https://openaitools.app/tool/autify-com) | 60,130 | +6% | Contact for Pricing | Automates web and mobile test creation and execution with AI, though less centered around manual test case organization. | [.md](https://openaitools.app/tool/autify-com.md) |
| 9 | [Shiplight AI](https://openaitools.app/tool/shiplight-ai) | 33,676 | -8.2% | Contact for Pricing | Agent-native end-to-end testing that maintains itself | [.md](https://openaitools.app/tool/shiplight-ai.md) |
| 10 | [QA.tech](https://openaitools.app/tool/qa-tech) | 30,550 | -4.4% | Paid, Contact for Pricing | Autonomous AI QA agents that verify your web and mobile app on every pull request | [.md](https://openaitools.app/tool/qa-tech.md) |

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Source: https://openaitools.app/compare/devzery-vs-qase

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