# Labelbox vs Scribbr

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. Scribbr records 7,530,803 monthly visits with +14.6% growth and Freemium pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [Scribbr](https://openaitools.app/tool/scribbr) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://www.scribbr.com |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI Writing, AI Proofreading, AI Plagiarism Checker, AI Writing Assistants |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 762,803 | 7,530,803 |
| MoM Growth Rate | -22.8% | +14.6% |
| Primary Market | United States | United States |
| Direct Visits | 370,024 | 2,472,819 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Labelbox

Labelbox occupies an unusual position in the AI stack: it does not primarily sell a chatbot or a generator, it builds the environments and data that models learn from plus the agents that take over recurring engineering and research work. The homepage claim is direct — frontier AI labs train on Labelbox environments and expert data, while engineering and research teams hand their recurring backlog to agents running on Recursion. A recent Series E of more than $100 million signals a heavily funded bet on that thesis.,For enterprises, the newer half of the product is Recursion. Agents are triggered by real signals — a failing build, a PagerDuty alert, a new dependency release, a fresh model checkpoint, or a Monday morning schedule — and then work in the background until the job is done. The examples the company promotes are concrete deliverables rather than summaries: a tested pull request with a preview link, a postmortem draft in Confluence with every event sourced, an ablation table naming the changes that mattered, or a patch for each exposed service after a critical CVE. A grader agent scores each run, and the graded session leaves behind memories, notes and skills that the next session reads before it acts.,The original foundation remains the data business: labeling, annotation, curation and model evaluation supported by expert human reviewers, used for computer vision, NLP, supervised fine-tuning, RLHF and red teaming. In practice the two halves reinforce each other, since the environments that produce high-quality training data are the same environments where agents learn to do real work. Pricing is enterprise-style, routed through sales conversations and shaped by data volume and agent usage, with no public self-serve tier.

**Pricing & Plans:** Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases.

- **Data labeling and expert annotation:** Structured annotation, curation, model evaluation and human-in-the-loop review across vision, language and generative tasks, used to build the training and eval data behind production models.
- **Autonomous agent sessions:** Recursion agents start on their own from builds, alerts, commits, checkpoints and schedules, then work in the background until the task is finished and reviewable.
- **Domain specialists by function:** Specialist agents cover software engineering, reliability, security, ML research, evals, R&D, product and finance workflows, from flaky test fixes to postmortem drafts and vulnerability patches.
- **Graded outcomes that compound:** Every agent run is scored by a grader, and graded sessions leave memories, notes and skills that the next session reads before acting, so quality compounds over time.
- **Native tool and data integrations:** Agents operate against the tools teams already use, including GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery, Databricks, Vercel and cloud providers.

**Strengths:** Covers both sides of the problem: training and eval data production plus agents that act on recurring work; Backed by a recent $100M+ Series E and adoption by frontier AI labs, indicating real funding and demand; Agent runs produce concrete deliverables with proof — tests, reruns, ablations — rather than unverified suggestions; Integrates with the toolchain teams already run: GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery and Databricks

**Limitations:** No self-serve pricing or open signup: everything routes through a sales conversation, which slows down evaluation; The platform assumes real engineering and research infrastructure (GitHub, cloud providers, data warehouses) to deliver value; Positioning has shifted quickly toward autonomous agent sessions, so teams wanting only labeling workflows may find it heavier than needed

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

## Scribbr

Scribbr was built around a simple promise: help students submit work they feel confident about. The core of the service is human proofreading and editing, delivered by a hand-picked pool of academic editors who go through an in-house training programme before they are allowed to take orders. Documents are returned with tracked changes, in-text comments and a short personal letter explaining the reasoning behind the main edits.

Alongside the human service, Scribbr offers a growing library of AI writing tools. The Academic Check bundles together grammar and language review, citation checking, plagiarism scanning and AI-content detection into a single upload, which is convenient when you want one pass over an entire paper rather than juggling separate tools. Individual utilities such as the citation generator for APA, MLA, Chicago, AMA, IEEE and ACS, the paraphrasing tool and the text summarizer can be used on their own without paying for an edit.

The platform also maintains a large free knowledge base of academic writing guides that has become one of the more popular ways students discover the brand. Pricing depends heavily on document length, chosen turnaround time and add-on checks, so the practical way to get a number is to upload a file and select services in the order flow.

**Pricing & Plans:** Freemium model. Free tools include the citation generator, grammar checker and summarizer. Human proofreading and editing, the plagiarism checker, AI detector, AI proofreader and Academic Check are paid per document, with the final price depending on page count, delivery speed and any add-on checks such as structure or clarity review.

- **Human proofreading and editing:** A vetted academic editor reviews your paper within hours and returns tracked changes, comments and an explanation letter.
- **Plagiarism checker:** Scans your document against a large web and publication database to surface potentially unoriginal passages before submission.
- **AI detector and AI humanizer:** Flags text likely generated by large language models and offers a rewriting mode aimed at making AI-assisted drafts sound more natural.
- **Citation generator:** Creates and verifies references in APA, MLA, Chicago, AMA, IEEE and ACS styles from a URL, DOI or title search.
- **Academic Check bundle:** Runs grammar, citations, clarity, plagiarism and AI-detection checks in a single upload of the whole document.

**Strengths:** Combines human editors with AI tools rather than relying on one alone; Strong editorial vetting process and a large pool of academic specialists; Free citation generator and knowledge base are genuinely useful on their own; Transparent turnaround options starting from a few hours

**Limitations:** Paid services are priced per document, which adds up for long theses; AI detector verdicts can still be disputed by institutions; Some premium checks require you to buy them alongside an editing order

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

## Frequently Asked Questions

### How do Labelbox and Scribbr compare in monthly traffic?

Labelbox has 762,803 monthly visits, while Scribbr has 7,530,803. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Labelbox has a month-over-month growth rate of -22.8%; Scribbr has +14.6%.

### How does pricing compare?

Labelbox: Contact for Pricing. Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases. Scribbr: Freemium. Freemium model. Free tools include the citation generator, grammar checker and summarizer. Human proofreading and editing, the plagiarism checker, AI detector, AI proofreader and Academic Check are paid per document, with the final price depending on page count, delivery speed and any add-on checks such as structure or clarity review.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Grammarly](https://openaitools.app/tool/grammarly) | 58,867,412 | -1.5% | Freemium | Delivers broader real-time grammar and tone correction across web apps, but lacks Scribbr's deep academic focus and citation formatting. | [.md](https://openaitools.app/tool/grammarly.md) |
| 2 | [QuillBot Paraphraser](https://openaitools.app/tool/quillbot-paraphraser) | 36,630,337 | +2.3% | Freemium | Provides robust paraphrasing and citation tools, but focuses less on comprehensive academic proofreading and human editing. | [.md](https://openaitools.app/tool/quillbot-paraphraser.md) |
| 3 | [ZeroGPT](https://openaitools.app/tool/zerogpt) | 32,864,541 | +19.7% | Freemium, Paid | AI content detection and a full writing toolkit in one place | [.md](https://openaitools.app/tool/zerogpt.md) |
| 4 | [GPTZero](https://openaitools.app/tool/gptzero-me) | 23,246,989 | +32.5% | Freemium, Paid | Focuses specifically on AI content detection and writing verification for educators, but lacks academic editing and proofreading workflows. | [.md](https://openaitools.app/tool/gptzero-me.md) |
| 5 | [LanguageTool](https://openaitools.app/tool/languagetool) | 5,707,795 | -4.2% | Freemium | AI grammar, spelling and style checker for 30+ languages | [.md](https://openaitools.app/tool/languagetool.md) |
| 6 | [Originality.ai](https://openaitools.app/tool/originality) | 2,049,639 | +2.8% | Paid | Provides enterprise-grade AI detection and plagiarism checking, but does not offer human academic proofreading or citation generation. | [.md](https://openaitools.app/tool/originality.md) |
| 7 | [Jenni](https://openaitools.app/tool/jenni) | 1,498,133 | +5.2% | Freemium | Offers specialized academic writing assistance and AI citation generation, but lacks Scribbr's human proofreading and formal editing services. | [.md](https://openaitools.app/tool/jenni.md) |
| 8 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines end-to-end computer vision workflows from annotation to model deployment, but lacks Labelbox's general enterprise agent orchestration. | [.md](https://openaitools.app/tool/roboflow.md) |
| 9 | [Appen](https://openaitools.app/tool/appen-com) | 665,840 | +0.2% | Contact for Pricing | Relies heavily on managed human-in-the-loop workforce services for data validation, offering less self-serve technical tooling than Labelbox. | [.md](https://openaitools.app/tool/appen-com.md) |
| 10 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | Delivers enterprise-grade labeling and model evaluation at massive scale, but often requires higher enterprise budgets than Labelbox. | [.md](https://openaitools.app/tool/scale.md) |

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Source: https://openaitools.app/compare/labelbox-vs-scribbr

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