# Labelbox vs SETI Protect

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. SETI Protect records 0 monthly visits with — growth and Contact for Pricing pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [SETI Protect](https://openaitools.app/tool/seti-protect) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://chromewebstore.google.com/detail/seti-protect/pgnfknjleldnfbjjjpjhkdbhekdbdffc |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI Face Recognition, AI Browsers |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 762,803 | 0 |
| MoM Growth Rate | -22.8% | — |
| Primary Market | United States | Global |
| Direct Visits | 370,024 | 0 |
| Review Score | 4.4 | 4.5 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Browser Extension |

## 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)

## SETI Protect

Most browser security assumes the person who typed the password is still the person using the browser five minutes later. SETI Protect attacks that assumption. Built by Smart Eye Technology, Inc. and distributed through the Chrome Web Store, the extension uses continuous facial tracking to keep verifying your identity while you browse, rather than checking once at login and then trusting whatever happens next.

That continuous model is what lets it address session jacking, where an attacker inherits a browser that is already authenticated, and remote desktop intrusions, where someone else gains control of a machine that is already signed in. In both cases a single login check offers no protection, because the login already happened. SETI Protect instead treats identity as an ongoing state to be re-confirmed from the webcam feed.

It is part of a broader biometric authentication framework from the same vendor, which the company describes as combining facial recognition with fingerprint, handwriting and voice verification for multi-factor protection. The store listing is update-maintained — version 9.0.1 shipped in late August 2025 — and carries a 4.8 out of five rating from a small early user base. Because it processes personally identifiable biometric information, the developer publishes a privacy policy and declares that data is not sold to third parties or used outside core functionality; as with any biometric tool, teams in regulated environments should review that policy and any spoof-resistance research before relying on it as a sole authentication factor.

**Pricing & Plans:** The extension itself installs free from the Chrome Web Store. Commercial and enterprise licensing is handled through the vendor, Smart Eye Technology, Inc., so pricing is quoted on contact rather than published as fixed tiers.

- **Continuous facial recognition:** Instead of verifying you once at sign-in, SETI Protect keeps checking the face at the keyboard for the whole session.
- **Session jacking protection:** Because authentication continues after login, a passerby who takes over an unlocked, already-signed-in browser is detected rather than trusted.
- **Remote desktop hack defense:** The extension is positioned to stop remote desktop takeovers, a common route for attackers into an authenticated browser.
- **Multi-modal biometric framework:** Built by Smart Eye Technology, whose framework layers facial recognition with fingerprint, handwriting and voice verification as biometric MFA/2FA.
- **Privacy disclosures:** The developer declares data is not sold to third parties and not repurposed outside the extension's core function, with a linked privacy policy.

**Strengths:** Continuous verification closes the gap left by one-time login checks; Directly targets session jacking and remote desktop takeover; Part of a wider biometric MFA framework covering several verification signals; Maintained listing with recent updates and a high user rating

**Limitations:** Uses a webcam for continuous facial tracking, which some users find intrusive in shared or public spaces; Third-party research on spoof resistance of facial MFA varies, so it should complement rather than replace strong passwords; Privacy-sensitive by nature: it processes personally identifiable biometric information; Small install base relative to mainstream security extensions

[Profile (Markdown)](https://openaitools.app/tool/seti-protect.md)

## Frequently Asked Questions

### How do Labelbox and SETI Protect compare in monthly traffic?

Labelbox has 762,803 monthly visits, while SETI Protect has 0. 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%; SETI Protect has —.

### 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. SETI Protect: Contact for Pricing. The extension itself installs free from the Chrome Web Store. Commercial and enterprise licensing is handled through the vendor, Smart Eye Technology, Inc., so pricing is quoted on contact rather than published as fixed tiers.

## 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 | [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) |
| 3 | [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) |
| 4 | [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) |
| 5 | [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) |
| 6 | [SocialFinder.ai](https://openaitools.app/tool/socialfinder-ai) | 250,665 | +47.7% | Paid | AI face search that turns one photo into someone's full digital footprint | [.md](https://openaitools.app/tool/socialfinder-ai.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 | [Face Search AI](https://openaitools.app/tool/face-search-ai) | 211,136 | +10% | Freemium, Paid | Reverse face search across the public web, with strong privacy guardrails | [.md](https://openaitools.app/tool/face-search-ai.md) |
| 9 | [FaceSearch](https://openaitools.app/tool/facesearch-ai) | 167,598 | +66.6% | Freemium | Upload one photo and find where that face appears across social media and the web | [.md](https://openaitools.app/tool/facesearch-ai.md) |
| 10 | [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) |

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Source: https://openaitools.app/compare/labelbox-vs-seti-protect

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