# Labelbox vs SuppCo

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. SuppCo records 207,874 monthly visits with -21.9% growth and Freemium pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [SuppCo](https://openaitools.app/tool/suppco) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://supp.co |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI Healthcare, AI Fitness, Other |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 762,803 | 207,874 |
| MoM Growth Rate | -22.8% | -21.9% |
| Primary Market | United States | United States |
| Direct Visits | 370,024 | 66,271 |
| Review Score | 4.4 | 4.1 |
| 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)

## SuppCo

SuppCo positions itself as a companion app for supplement users rather than a shop. You add the products you already take, and SuppCo rates each one with its TrustScore system, a 29-attribute quality measure that weighs manufacturing standards, third-party testing, label accuracy and inactive ingredients. The score and the underlying evidence are shown openly, so a 9.8 "Excellent" rating on a fish oil is explained rather than asserted.

The other half of the product is personalisation. Stack analysis reviews your whole regimen for nutrient coverage, dosing and redundancy, then compares it against your goals and returns a StackScore with specific suggestions. SuppCo's expert panel, which includes physicians and nutrition coaches known for their work in functional medicine, contributes protocols for goals such as longevity, gut health, fitness, weight management and fertility, and a research center summarises what thousands of studies say about individual nutrients and popular ingredients.

Alongside the app, SuppCo runs a Buying Club that sells vetted products directly and returns a share of spend as credits, plus a community and editorial layer. The service is free to use, with an optional Pro subscription for deeper personalisation, and SuppCo now operates as part of Function following that acquisition.

**Pricing & Plans:** Freemium. SuppCo is free for all users, including the stack tracker, TrustScore product ratings and research content. An optional Pro subscription unlocks advanced personalization tools, and the SuppCo Buying Club offers 30% back in Supp Credits on purchases.

- **TrustScore® quality ratings:** Scan or search products to see a quality rating built from 29 attributes covering manufacturing standards, testing benchmarks and inactive ingredients.
- **Personalized stack analysis:** Get a StackScore for your routine along with nutrient-level coverage, dosing feedback and gap analysis against your health goals.
- **Expert-designed protocols:** Follow regimens designed by clinicians and functional-medicine experts for goals like longevity, gut health, fitness, weight management and fertility.
- **Tracker with reminders:** Smart scheduling, reminders and daily intake logging so you actually stick to your supplement routine.
- **Research center and community:** Browse nutrient explainers, goal guides and protocols informed by thousands of published studies, plus a members' community.

**Strengths:** TrustScore turns supplement quality into a plain numeric rating with visible criteria; Stack analysis catches overlaps, dosing issues and coverage gaps across a whole routine; Protocols contributed by named, credentialed experts rather than anonymous listicles; Free core tier with no paywall on basic tracking and product research

**Limitations:** Health guidance is educational and not a substitute for professional medical advice; Pro tier required for the most advanced personalization features; Vendor-supplied listings and scores may not cover every niche or regional brand; App-centric experience, so desktop-only users get less value

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

## Frequently Asked Questions

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

Labelbox has 762,803 monthly visits, while SuppCo has 207,874. 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%; SuppCo has -21.9%.

### 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. SuppCo: Freemium. Freemium. SuppCo is free for all users, including the stack tracker, TrustScore product ratings and research content. An optional Pro subscription unlocks advanced personalization tools, and the SuppCo Buying Club offers 30% back in Supp Credits on purchases.

## 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 | [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) |
| 7 | [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) |
| 8 | [AlterMe](https://openaitools.app/tool/alter) | 108,996 | -11.4% | Paid | Builds personalized wellness plans from DNA and biometrics, but focuses less on dedicated supplement stack optimization. | [.md](https://openaitools.app/tool/alter.md) |
| 9 | [Confident AI](https://openaitools.app/tool/confident-ai) | 83,400 | -3.3% | Freemium, Paid, Contact for Pricing | Focuses strictly on LLM evaluation, testing, and observability rather than raw data annotation and training dataset curation. | [.md](https://openaitools.app/tool/confident-ai.md) |
| 10 | [Empirical Health](https://openaitools.app/tool/empirical-health) | 70,517 | -28.8% | Paid | Pairs biomarker testing with wellness plans, but does not provide specific supplement quality ratings or stack dosing. | [.md](https://openaitools.app/tool/empirical-health.md) |

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

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