# Fork Wise vs Labelbox

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

| Metric | [Fork Wise](https://openaitools.app/tool/fork-wise) | [Labelbox](https://openaitools.app/tool/labelbox) |
| :--- | :--- | :--- |
| Website URL | https://apps.apple.com/gb/app/fork-wise/id6736621740 | https://labelbox.com |
| Categories | AI Cooking Assistant, AI OCR, AI Fitness | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools |
| Pricing Model | Freemium | Contact for Pricing |
| Monthly Visits | 0 | 762,803 |
| MoM Growth Rate | — | -22.8% |
| Primary Market | Global | United States |
| Direct Visits | 0 | 370,024 |
| Review Score | 3.8 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | App | Website |

## Fork Wise

Fork Wise is a consumer iOS app for people who care what is in their food but do not want to interrogate a waiter about every dish. You point your camera at a menu — or at a shelf of products in a grocery store — and the app uses AI menu analysis to break each dish down into plain language, matching items against the macros, health goals, dietary preferences and exclusions in your profile.

Rather than showing a wall of numbers, Fork Wise surfaces what matters for the decision in front of you: allergen badges so dietary must-haves stand out, filters for ingredients you want to avoid, and sorting by calories, protein, carbohydrates or fat when you are tracking targets. Multi-page menus can be captured while a scan is running and merged into one result, and notes from previous scans travel with you so you do not re-learn the same menu.

The app also includes accessibility-minded touches: dishes can be read aloud with clear pronunciation, and menu text in another language is accompanied by a line in your own language. Fork Wise is a paid/freemium app distributed on the Apple App Store by developer Zubin Ghai, with a free allowance of scans and an in-app purchase to unlock unlimited scanning. The developer explicitly notes it is an information tool, not medical or allergy advice.

**Pricing & Plans:** Free to download with a free tier of 10 menu scans; an in-app purchase (listed at around £0.99 in the UK App Store) unlocks unlimited scans.

- **AI menu analysis from a photo:** Take a photo of any written menu and Fork Wise reads the page, breaks dishes into plain language and rates how well they match your profile.
- **Allergen badges and filters:** Allergens and unwanted ingredients are flagged with clear badges, and you can filter them out of the results.
- **Macro and calorie sorting:** Sort dishes by calories, protein, carbohydrates and fat so you can hit specific nutritional targets.
- **Multi-page scans and saved notes:** Scan multi-page menus, add pages during a run and merge them into one result, and keep notes from past scans.
- **Voice readouts and translation:** Tap and hold dishes to hear them read aloud, and see translation lines for menus written in another language.

**Strengths:** Turns an unreadable menu into clear, personalised recommendations in seconds; Allergen badges and macro sorting cover both safety and nutrition goals; Works anywhere, including menus in other languages, with read-aloud support; Lightweight app (about 3.5 MB) with a generous 10-scan free tier

**Limitations:** Only available on Apple platforms (iPhone, iPad, Apple-silicon Mac); The developer states it is not a substitute for medical or allergy advice; Accuracy depends on photo quality and the clarity of the printed menu

[Profile (Markdown)](https://openaitools.app/tool/fork-wise.md)

## 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)

## Frequently Asked Questions

### How do Fork Wise and Labelbox compare in monthly traffic?

Fork Wise has 0 monthly visits, while Labelbox has 762,803. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Fork Wise has a month-over-month growth rate of —; Labelbox has -22.8%.

### How does pricing compare?

Fork Wise: Freemium. Free to download with a free tier of 10 menu scans; an in-app purchase (listed at around £0.99 in the UK App Store) unlocks unlimited scans. 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.

## 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 | [DishGen](https://openaitools.app/tool/dishgen) | 91,986 | +1.1% | Freemium, Free Trial | Turn your ingredients and cravings into custom AI recipes and meal plans | [.md](https://openaitools.app/tool/dishgen.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 | [Flavorish](https://openaitools.app/tool/flavorish) | 68,000 | +16.3% | Freemium | Save recipes from anywhere and turn them into meal plans and grocery lists | [.md](https://openaitools.app/tool/flavorish.md) |

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Source: https://openaitools.app/compare/fork-wise-vs-labelbox

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