# Eraser vs EvalCore

Eraser records 534,396 monthly visits with -23.6% month-over-month growth and Freemium, Paid, Contact for Pricing pricing. EvalCore records 0 monthly visits with 0% growth and Free pricing.

| Metric | [Eraser](https://openaitools.app/tool/eraser) | [EvalCore](https://openaitools.app/tool/evalcore) |
| :--- | :--- | :--- |
| Website URL | https://www.eraser.io | https://evalcore.cc |
| Categories | AI Diagram Generator, AI Copilot, AI Design Generator, AI Documents Generator | AI Testing, AI Developer Tools, Large Language Models (LLMs), AI Agent |
| Pricing Model | Freemium, Paid, Contact for Pricing | Free |
| Monthly Visits | 534,396 | 0 |
| MoM Growth Rate | -23.6% | 0% |
| Primary Market | India | Global |
| Direct Visits | 267,661 | 0 |
| Review Score | 4.6 | 4.8 |
| Saved Count | 3 | 0 |
| Supported Platforms | Website | Website |

## Eraser

Eraser is a technical design platform aimed at the people who document architecture: enterprise architects, DevOps and platform engineers, consultants, and software teams. The core promise is speed without sloppiness, so instead of dragging boxes for hours you describe the system or point Eraser at a source of truth such as code, a cloud account, a CMDB, or a spreadsheet, and it produces a diagram that already follows sensible layout rules.

Beyond static images, Eraser supports interactive maps that zoom from a company-wide view down into a single service, guided explainers that walk teammates through a system, and AI documents for design docs and technical documentation. Team governance features such as shared style presets, naming rules, and reference architectures keep output consistent as more people create diagrams. An open-source agent toolkit and MCP server let tools like Claude, Cursor, and ChatGPT create, search, and export diagrams programmatically.

Prices are organized in tiers that include a free entry point, paid plans, and enterprise agreements, with multi-tenant, single-tenant, and self-hosted deployment options for larger organizations. Security posture includes SOC 2 Type 2 certification and SAML SSO.

**Pricing & Plans:** Freemium with paid plans and custom enterprise pricing. A free tier and free tools such as DiagramGPT are available, while paid individual and team plans plus enterprise agreements cover advanced governance, security, and deployment options; check the pricing page for current rates.

- **AI diagram generation:** Generate architecture diagrams, flowcharts, sequence diagrams, and BPMN from a text prompt, code, Terraform, or an uploaded PDF, Word, Excel, PowerPoint, Draw.io, or Visio file.
- **Maps from live systems:** Build interactive maps that sync with cloud accounts, repositories, and internal catalogs so the picture stays close to the real environment, with drill-down from org level to a single container.
- **Diagram-as-code integrations:** Paste code or connect private and public Git repositories, Confluence, Notion, VS Code, and GitHub to keep diagrams grounded in actual implementation.
- **Open-source agent toolkit and MCP server:** Run the agent toolkit in your own infrastructure under an MIT license and let MCP-compatible clients create, search, update, and export diagrams with OAuth or API tokens.
- **Team style governance:** Apply presets, naming and notation rules, and reference architectures so every teammate's diagram ships on-brand and consistent.

**Strengths:** Turns prompts, code, and files into properly laid-out diagrams instead of raw box-and-arrow output; Interactive maps and explainers make complex systems understandable to non-architects; MCP server and open-source toolkit fit agent-driven and self-hosted workflows; Enterprise controls such as SSO, SAML, and SOC 2 Type 2 certification

**Limitations:** Heaviest value comes with team and governance features that need setup; Advanced mapping and self-hosted deployment are aimed at larger organizations rather than solo users

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

## 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)

## Frequently Asked Questions

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

Eraser has 534,396 monthly visits, while EvalCore has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Eraser has a month-over-month growth rate of -23.6%; EvalCore has 0%.

### How does pricing compare?

Eraser: Freemium, Paid, Contact for Pricing. Freemium with paid plans and custom enterprise pricing. A free tier and free tools such as DiagramGPT are available, while paid individual and team plans plus enterprise agreements cover advanced governance, security, and deployment options; check the pricing page for current rates. 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.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Miro](https://openaitools.app/tool/miro) | 30,749,206 | +1.7% | Freemium, Contact for Pricing | Offers an expansive infinite canvas for team brainstorming and visual workshops, but lacks Eraser's code-to-diagram automation. | [.md](https://openaitools.app/tool/miro.md) |
| 2 | [Napkin AI](https://openaitools.app/tool/napkin) | 1,029,978 | -17.5% | Freemium | Automatically embeds visual diagrams directly inside text documents, though it lacks Eraser's specialized cloud architecture focus. | [.md](https://openaitools.app/tool/napkin.md) |
| 3 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 4 | [EdrawMax](https://openaitools.app/tool/edrawmax-com) | 301,707 | -6.5% | Paid | Provides extensive drag-and-drop shapes and templates for general diagrams, but weaker automated code-to-diagram capabilities than Eraser. | [.md](https://openaitools.app/tool/edrawmax-com.md) |
| 5 | [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) |
| 6 | [Cloudairy](https://openaitools.app/tool/cloudairy) | 179,162 | -13% | Freemium, Contact for Pricing | Combines team whiteboarding, documentation, and diagramming in one platform, but less tailored for automated codebase architecture. | [.md](https://openaitools.app/tool/cloudairy.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [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) |
| 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/eraser-vs-evalcore

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