# Labelbox vs Namefi

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. Namefi records 27,219 monthly visits with +8.7% growth and Freemium pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [Namefi](https://openaitools.app/tool/namefi) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://www.namefi.io |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | Blockchain, Web3, NFTs, AI Description Generator |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 762,803 | 27,219 |
| MoM Growth Rate | -22.8% | +8.7% |
| Primary Market | United States | South Korea |
| Direct Visits | 370,024 | 10,558 |
| Review Score | 4.4 | 3.9 |
| 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)

## Namefi

Namefi reimagines what a domain registrar can be. It is an ICANN-accredited registrar, so it can handle standard registration, transfers, and renewals, but it adds an onchain layer: domain names can be tokenized as NFTs on Ethereum or Base, which makes ownership transferable and tradable like a digital asset. Payments work with credit cards as well as stablecoins such as USDC and crypto like ETH.

A major focus is agentic workflows. Namefi exposes an MCP server, a CLI, and llms.txt documentation so an AI agent can search, buy, and pay for a domain in one flow over the x402 protocol, with no account or stored card required. The platform also offers tools like Search with AI, domain collections, wishlists, a marketplace, and DNS features including AutoENS. An AI-powered DNS setup assistant helps you configure records even without DNS expertise.

Beyond ownership, Namefi supports teams with role-based sharing and subdomain issuing, and it is moving toward giving each AI agent its own subdomain with spend limits, expiry, and instant revoke. Pricing follows a freemium model with registration and renewal fees typical of a registrar, often at competitive rates compared with mainstream registrars.

**Pricing & Plans:** Freemium. Domain registration and renewal are priced per TLD, and the platform supports payment by credit card, stablecoins (USDC), and ETH. Some products, such as the free hostname for dynamic DNS, are offered at no cost; check the site for current TLD pricing.

- **Tokenized Domains as NFTs:** Mint a domain onchain on Ethereum or Base so ownership can be transferred or traded instantly, similar to a digital asset.
- **AI Agent and MCP Support:** An MCP server, CLI, WebMCP, and llms.txt let AI agents search, buy, and manage domains and DNS without a traditional account.
- **Agent-Friendly Payment:** Agents can pay over the x402 protocol in USDC, while human users can check out with a card, stablecoins, or ETH.
- **Marketplace and Collections:** Browse domain collections, build wishlists, and trade on an outbound and general domain marketplace.
- **DNS Tools and AutoENS:** An AI DNS setup assistant and AutoENS simplify record configuration and connect a name to your website, email, and wallet.

**Strengths:** ICANN-accredited registrar with an added onchain tokenization layer; First-class support for AI agents via MCP, CLI, and x402 payments; Pay with credit card, stablecoins, or ETH; Team sharing, subdomain issuing, and DNS assistance tools

**Limitations:** Tokenized domain concepts can be complex for newcomers; Some advanced features such as agent subdomains with limits are still marked coming soon; Onchain transactions may involve gas and network considerations

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

## Frequently Asked Questions

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

Labelbox has 762,803 monthly visits, while Namefi has 27,219. 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%; Namefi has +8.7%.

### 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. Namefi: Freemium. Freemium. Domain registration and renewal are priced per TLD, and the platform supports payment by credit card, stablecoins (USDC), and ETH. Some products, such as the free hostname for dynamic DNS, are offered at no cost; check the site for current TLD pricing.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [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) |
| 2 | [Namelix](https://openaitools.app/tool/namelix) | 677,565 | -14.6% | Free | Free AI naming engine for short, brandable business names | [.md](https://openaitools.app/tool/namelix.md) |
| 3 | [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) |
| 4 | [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) |
| 5 | [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) |
| 6 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 7 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | Specializes in advanced computer vision and physical AI data pipelines, though with a narrower focus than general text-and-image labeling. | [.md](https://openaitools.app/tool/encord-com.md) |
| 8 | [Nametastic](https://openaitools.app/tool/nametastic) | 148,843 | +98.8% | Freemium | AI naming that only shows domains you can actually register | [.md](https://openaitools.app/tool/nametastic.md) |
| 9 | [Label Studio](https://openaitools.app/tool/label-studio) | 137,199 | -16.1% | Contact for Pricing, Free | Provides a flexible open-source alternative for custom data labeling, but requires self-hosting and manual infrastructure maintenance. | [.md](https://openaitools.app/tool/label-studio.md) |
| 10 | [Surf](https://openaitools.app/tool/surf) | 116,252 | -18.9% | Free, Pro, Max, API credits | Institution-grade crypto and equities intelligence, delivered through a chat-style AI analyst. | [.md](https://openaitools.app/tool/surf.md) |

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

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