# Labelbox vs Runable

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. Runable records 1,048,370 monthly visits with -1.9% growth and Freemium pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [Runable](https://openaitools.app/tool/runable) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://runable.com |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI Agent, AI Assistant, AI Productivity Tools, AI Workflow |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 762,803 | 1,048,370 |
| MoM Growth Rate | -22.8% | -1.9% |
| Primary Market | United States | United States |
| Direct Visits | 370,024 | 341,714 |
| Review Score | 4.4 | 3.8 |
| Saved Count | 0 | 5 |
| 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)

## Runable

Runable is positioned as a general AI agent rather than a single-purpose generator. You start with a sentence describing the outcome you want, and the agent plans the steps, produces the artefacts and keeps them updated. The main surfaces are websites and app building, slide and carousel creation, image and video generation, and document and research work, all reachable from the same conversation.

Beyond one-off creation, Runable emphasises running and growing what you have already built. Scheduled tasks can handle recurring jobs such as reminders, follow-ups and deadline tracking, agent skills let you save repeatable instructions, and a plugin library extends what the agent can touch. Its personal assistant can be reached through channels like Slack, Teams, Telegram, iMessage and Discord, and native apps exist for iOS, iPad, macOS, Android and Windows.

The platform is credit-based. The Free tier provides 1,500 credits daily, Pro raises the monthly allowance and unlocks higher limits plus multi-modal chat, and Max targets heavy users who want the widest limits. A free tier plus published plan pricing makes it straightforward to test before committing.

**Pricing & Plans:** Freemium with three published tiers. Free includes 1,500 credits per day plus website and app building, slides, carousels, image creation and document research. Pro is about $20/month with 25,000 monthly credits plus the daily allowance, video creation, 100+ curated workflows and the cross-channel personal assistant. Max is about $100/month with 150,000 monthly credits, unlimited Ask-mode chats and the highest limits. Annual billing and limited-time ad-credit offers are advertised.

- **Websites and app builder:** Generate websites and app builds from a prompt, with options for a free database, analytics, Stripe integration and mobile app packaging.
- **Slides and carousels:** Turn a brief into polished slide decks and social carousels, then iterate with the agent until they are ready to present.
- **Images, video and documents:** Produce images and video assets, plus research-backed documents and reports, without switching between separate tools.
- **Agent skills, plugins and scheduled tasks:** Run frequent tasks on a schedule, define reusable agent skills, and extend behaviour with plugins and curated workflows.
- **Cross-channel assistant:** Reach the agent through Slack, Microsoft Teams, Telegram, iMessage and Discord, with desktop and mobile apps for each major platform.

**Strengths:** One agent covers websites, slides, videos, documents and research; Generous free tier with 1,500 credits per day; Cross-channel access through the apps you already use; Reusable skills and scheduled tasks for ongoing work

**Limitations:** Advanced agent capabilities are gated behind the Pro and Max tiers; Credit-based limits can be consumed quickly by heavy builds; The breadth of features means a learning curve before you get the most out of it; Output quality depends heavily on how precisely you brief the agent

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

## Frequently Asked Questions

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

Labelbox has 762,803 monthly visits, while Runable has 1,048,370. 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%; Runable has -1.9%.

### 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. Runable: Freemium. Freemium with three published tiers. Free includes 1,500 credits per day plus website and app building, slides, carousels, image creation and document research. Pro is about $20/month with 25,000 monthly credits plus the daily allowance, video creation, 100+ curated workflows and the cross-channel personal assistant. Max is about $100/month with 150,000 monthly credits, unlimited Ask-mode chats and the highest limits. Annual billing and limited-time ad-credit offers are advertised.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Claude](https://openaitools.app/tool/claude-2) | 1,253,439,413 | +23.8% | Freemium | Provides superior coding and interactive artifact generation, but lacks dedicated multi-app workflow automation pipelines. | [.md](https://openaitools.app/tool/claude-2.md) |
| 2 | [Gamma AI](https://openaitools.app/tool/gamma-ai-1) | 20,808,177 | -1.4% | Freemium | Creates much better styled presentations and web pages visually, but lacks general workflow automation and agent execution. | [.md](https://openaitools.app/tool/gamma-ai-1.md) |
| 3 | [Manus](https://openaitools.app/tool/manus) | 19,195,779 | -1.7% | Free Trial | Offers more robust autonomous browser execution for complex tasks, but lacks Runable's broad digital asset templates. | [.md](https://openaitools.app/tool/manus.md) |
| 4 | [WorkBuddy](https://openaitools.app/tool/workbuddy) | 2,341,262 | +43.9% | Freemium | Delivers polished office reports and research summaries quickly, but lacks deep multi-step agentic browser control. | [.md](https://openaitools.app/tool/workbuddy.md) |
| 5 | [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) |
| 6 | [Skywork.ai](https://openaitools.app/tool/skywork-ai) | 1,021,069 | -11.8% | Freemium | Stronger at converting files directly into structured documents and slide decks, but offers less general workflow automation. | [.md](https://openaitools.app/tool/skywork-ai.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Taskade](https://openaitools.app/tool/taskade) | 539,714 | -9.4% | Freemium | Combines project management with no-code AI app builders, though it feels more structured and less purely prompt-driven. | [.md](https://openaitools.app/tool/taskade.md) |
| 10 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Offers robust multimodal annotation and workflow automation, featuring slightly more intuitive data curation pipelines for computer vision teams. | [.md](https://openaitools.app/tool/super-annotate.md) |

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

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)