# EvalCore vs Katalon

EvalCore records 0 monthly visits with 0% month-over-month growth and Free pricing. Katalon records 158,090 monthly visits with -29.6% growth and Freemium, Free Trial, Paid, Contact for Pricing pricing.

| Metric | [EvalCore](https://openaitools.app/tool/evalcore) | [Katalon](https://openaitools.app/tool/katalon-studio) |
| :--- | :--- | :--- |
| Website URL | https://evalcore.cc | https://www.katalon.com |
| Categories | AI Testing, AI Developer Tools, Large Language Models (LLMs), AI Agent | AI Testing, No-Code&Low-Code, AI Code Generator, AI Developer Tools |
| Pricing Model | Free | Freemium, Free Trial, Paid, Contact for Pricing |
| Monthly Visits | 0 | 158,090 |
| MoM Growth Rate | 0% | -29.6% |
| Primary Market | Global | Vietnam |
| Direct Visits | 0 | 87,966 |
| Review Score | 4.8 | 4.5 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## EvalCore

EvalCore solves a common failure mode in AI engineering: you tweak a prompt, swap a model, or bump a dependency, and something quietly breaks in production. Instead of trying to re-run expensive, non-deterministic model calls in CI, EvalCore treats AI behaviour like a snapshot. An eval is just a YAML file describing a target and a JSONL dataset, with scorers stacked on top to define what "good" means.

The first run happens live against a real model — anything OpenAI-compatible, vLLM, Ollama, a custom REST API, a shell command, or OpenTelemetry/OpenInference traces. Every request and response is written to a local SQLite cassette, keyed by a hash of the canonical request, along with token and cost figures on the summary. From then on, CI replays those recordings byte-for-byte with `--cache replay`: no network, no API keys, no flaky judge model, and identical inputs always produce identical verdicts.

Because the cassette is committed to your repository, a `--baseline main` comparison fails only on genuine regressions, and the process exit code gates the pipeline. Trials, model comparisons, agent traces, gates, and reports are all a few lines of YAML or a flag rather than a framework. It ships as one small Rust binary, works with any language on the other side of the target, and collects no telemetry.

**Pricing & Plans:** Free and open source under the Apache-2.0 licence, with $0 cost in CI thanks to offline cassette replay. Install via cargo or prebuilt binaries; no signup, no server and no telemetry.

- **Record once, replay forever:** A live run captures every model request and response into a local SQLite cassette that CI can replay offline and deterministically at zero cost.
- **Anything can be a target:** Point EvalCore at OpenAI-compatible endpoints, vLLM, Ollama, your own REST APIs, shell commands, or OTel/OpenInference traces — no SDK required.
- **Scorers that define 'good':** Stack contains, judge-rubric and other scorers in YAML to express exactly what a correct answer looks like for each case.
- **Regression gates and baselines:** Compare against a baseline branch so only real regressions fail, and let the process exit code gate your pull requests.
- **Cost, tokens and reports built in:** Every summary reports token usage and spend for live runs, while trials, model comparisons and history give you a clear picture over time.

**Strengths:** Genuinely free and open source under Apache-2.0, with no usage-based pricing; Deterministic offline replay removes flaky, expensive model calls from CI; Single dependency-free binary that works regardless of your app's language; Configuration is plain YAML plus JSONL, so suites are easy to review and version

**Limitations:** Requires a Rust toolchain or a prebuilt binary and comfort with the command line; Cassettes must be recorded live first, so initial setup needs real API access; No hosted dashboard — results and history live in your repo and CI logs

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

## Katalon

Katalon bundles four connected products under one umbrella it calls Katalon True: Katalon Studio for authoring tests, TestOps for test management and manual testing, TestCloud for running suites on real browsers and devices, and TrueTest for observing real user behaviour in production and spotting coverage gaps. Because authoring, tracking and execution live in the same system of record, requirements, test cases, evidence, defects and release health can be traced in one auditable place rather than across spreadsheets and disconnected tools.

The platform is explicitly built to support a mixed-skill team. Testers who prefer visual tooling can author tests with record-and-playback or keyword-driven steps, developers can drop into scripted full-code mode, and AI agents cover the middle ground by drafting test cases from a requirement, a Jira ticket or a natural-language prompt. Self-healing retries alternative locators when the UI changes, and failure analysis explains root causes in plain language so a broken run can be repaired and reviewed rather than quietly re-recorded.

Katalon also leans into interoperability. It supports Playwright scripts alongside native Katalon tests and consolidates the results in TestOps, exposes an MCP server so external coding agents such as Copilot, Cursor or Claude can drive test runs, and lets organisations bring their own AI provider (OpenAI, Azure OpenAI, Google Gemini or AWS Bedrock) instead of being locked to a single model vendor.

**Pricing & Plans:** Freemium with a free tier for local authoring and execution, plus a 30-day free trial of paid features. Professional is roughly $1,800 per seat per year (around $150 per seat per month) with AI agents, MCP server access, desktop testing, parallel execution and CI/CD integrations. Enterprise is quoted on contract and adds SSO/SAML, SCIM provisioning, RBAC, audit logs, private cloud or on-premises deployment, hybrid licensing and premium support.

- **Katalon AI agents and self-healing:** Generate automation scripts and test cases from natural language or tickets, get plain-language explanations, and let self-healing retry alternative locators when the UI changes so suites keep running through small front-end edits.
- **Unified multi-application testing:** Cover web, API, mobile (Android and iOS) and Windows desktop applications inside one authoring environment, with record-and-playback, data-driven testing, BDD/Cucumber support and a dual-mode debugger.
- **TestOps management and analytics:** Plan cycles, map requirements to cases, track coverage and flakiness, link defects in Jira, and gate releases using a shared live report that unifies manual, automated and AI-generated runs.
- **TestCloud execution environments:** Run suites in parallel on real browsers, real iOS and Android devices, or your own CI runners and on-premise Runtime Engine, with lane-based parallel execution for faster coverage.
- **MCP server and bring-your-own-AI:** Connect Katalon to external coding agents via MCP, and choose between the built-in Katalon AI Service or your own provider such as OpenAI, Azure OpenAI, Google Gemini or AWS Bedrock.

**Strengths:** Supports no-code, low-code and full-code authoring in one product, so mixed-skill QA teams do not need separate tools; Genuinely end-to-end scope: authoring, test management, cloud execution and production insights share a single system of record; Strong interoperability story, including Playwright support, an MCP server and a choice of AI providers; Free tier plus a 30-day trial makes it easy to evaluate before committing budget

**Limitations:** Professional pricing at roughly $150 per seat per month is steep for small teams; Commercial desktop testing, parallel execution and CI/CD execution are gated behind paid tiers; Enterprise capabilities such as SSO, audit logs and on-premises deployment require a sales conversation and annual contract

[Profile (Markdown)](https://openaitools.app/tool/katalon-studio.md)

## Frequently Asked Questions

### How do EvalCore and Katalon compare in monthly traffic?

EvalCore has 0 monthly visits, while Katalon has 158,090. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

EvalCore has a month-over-month growth rate of 0%; Katalon has -29.6%.

### How does pricing compare?

EvalCore: Free. Free and open source under the Apache-2.0 licence, with $0 cost in CI thanks to offline cassette replay. Install via cargo or prebuilt binaries; no signup, no server and no telemetry. Katalon: Freemium, Free Trial, Paid, Contact for Pricing. Freemium with a free tier for local authoring and execution, plus a 30-day free trial of paid features. Professional is roughly $1,800 per seat per year (around $150 per seat per month) with AI agents, MCP server access, desktop testing, parallel execution and CI/CD integrations. Enterprise is quoted on contract and adds SSO/SAML, SCIM provisioning, RBAC, audit logs, private cloud or on-premises deployment, hybrid licensing and premium support.

## 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 | Advanced conversational QA agent that builds and heals tests seamlessly, but has a less traditional scripted IDE workflow. | [.md](https://openaitools.app/tool/kaneai.md) |
| 2 | [Qase](https://openaitools.app/tool/qase) | 319,213 | -25.5% | Freemium, Free Trial, Contact for Pricing, Free | Ship with confidence: one system of record for manual, automated, and CI tests | [.md](https://openaitools.app/tool/qase.md) |
| 3 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.md) |
| 4 | [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) |
| 5 | [Mindgard](https://openaitools.app/tool/mindgard) | 153,455 | +1.3% | Contact for Pricing | Attack-led AI security testing and red teaming | [.md](https://openaitools.app/tool/mindgard.md) |
| 6 | [Future AGI](https://openaitools.app/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | Build, simulate, evaluate and monitor self-improving AI agents | [.md](https://openaitools.app/tool/future-agi.md) |
| 7 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Evaluate, monitor, and govern your AI applications in production | [.md](https://openaitools.app/tool/maxim-ai.md) |
| 8 | [TestSprite](https://openaitools.app/tool/testsprite) | 114,205 | +15.8% | Freemium | Automates test suite generation and regression testing efficiently, but with less emphasis on manual test planning. | [.md](https://openaitools.app/tool/testsprite.md) |
| 9 | [testRigor](https://openaitools.app/tool/testrigor-com) | 105,865 | -2.7% | Free Trial, Contact for Pricing, Free | Writes and maintains robust tests entirely in plain English, but offers fewer legacy low-code scripting features. | [.md](https://openaitools.app/tool/testrigor-com.md) |
| 10 | [Maestro Studio Desktop Beta](https://openaitools.app/tool/maestro-studio-desktop-beta) | 102,589 | -22.4% | Freemium | Open-source, human-readable UI testing for mobile and web | [.md](https://openaitools.app/tool/maestro-studio-desktop-beta.md) |

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Source: https://openaitools.app/compare/evalcore-vs-katalon-studio

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