# Labelbox vs Ultimaps

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. Ultimaps records 151,723 monthly visits with -11.3% growth and Freemium pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [Ultimaps](https://openaitools.app/tool/ultimaps) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://ultimaps.com |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI Map Generator, AI Charting, AI Design Generator, AI Graphic Design |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 762,803 | 151,723 |
| MoM Growth Rate | -22.8% | -11.3% |
| Primary Market | United States | United States |
| Direct Visits | 370,024 | 20,284 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 0 | 2 |
| 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)

## Ultimaps

Ultimaps is an online map maker built for people who have data in a spreadsheet and need it on a map without learning GIS. You begin by selecting one of more than 200 pre-built vector maps — the world, a continent, any country, US states, individual states by county, or ZIP codes — each split into administrative regions you can color individually. From there you either shade regions by hand or bring in data by pasting from Excel, uploading a CSV, connecting Google Sheets or Notion, or typing a natural-language prompt like "color states by population." The tool matches your values to the right regions even when the formatting is messy, then generates a color scale and legend automatically.

For shareable output, Ultimaps converts any map into a live, embeddable experience. Tooltips and popups are populated from your data columns, so a single template covers every region, and visitors can hover, click through links, and pan or zoom. Publishing produces a shareable link or an embed code; in Notion, WordPress, Ghost and Substack you can simply paste the link and it renders as the live map, with edits reflected after publishing and no new code to re-paste. Static exports cover high-resolution PNG, SVG and PDF for reports, slides and print.

The platform also advertises an integration that lets users make maps from their data inside ChatGPT, plus quick single-purpose tools such as Color a Map, Map Maker, US Map Maker and ZIP Code Map Maker. Pricing is freemium: unlimited maps and importing are free, free PNG exports carry a small credit, and the Pro plan removes branding, unlocks vector and 6x-resolution exports, adds templates, duplicates, larger lookup and AI request allowances, and includes priority support. Custom maps for regions Ultimaps does not cover are available as a paid service. The company reports 25,000+ monthly users and a 4.8 out of 5 rating from 72 reviews.

**Pricing & Plans:** Freemium. The Free plan offers unlimited maps with Excel, CSV, Sheets and Notion imports, 100 address lookups and 20 AI requests per month, and PNG export with a small ultimaps.com credit. Pro (roughly EUR41.58/month billed yearly, around EUR49 monthly) adds unbranded exports, 6x-resolution PNG plus SVG and PDF, unbranded interactive maps, 5,000 lookups and 500 AI requests monthly, and priority support. Custom plans and single-map exports (about EUR12.50 per map) are also offered.

- **200+ Ready-Made Vector Maps:** Choose from world, continent, country, US state, county and ZIP code maps, each divided into regions you can color individually.
- **Spreadsheet & AI Data Import:** Paste from Excel, upload CSV, connect Google Sheets or Notion, or type a prompt like "color states by population" and let the AI map it.
- **Automatic Scales and Legends:** Smart color scaling picks palettes and breakpoints for your dataset and generates a matching legend without manual configuration.
- **Interactive Embeds:** Publish a live map with tooltips, popups, click-through links, pan and zoom, then embed it via one line of code or by pasting the link into Notion, WordPress, Ghost or Substack.
- **Pins and Annotations:** Geocode addresses into pins, group nearby locations with numbered markers, add annotations, and color-code regions by category or value.

**Strengths:** Very low friction: no account needed to start and no GIS skills required; Imports directly from Excel, CSV, Google Sheets and Notion with fuzzy region matching; Automatic color scales and legends save manual design work; Interactive embeds with tooltips and popups work across major CMS platforms

**Limitations:** Publishing interactive maps and unbranded exports require a paid tier; Free interactive maps display a small ultimaps.com credit; Free plan caps address lookups and AI requests each month; Advanced custom regions and themes need a bespoke arrangement

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

## Frequently Asked Questions

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

Labelbox has 762,803 monthly visits, while Ultimaps has 151,723. 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%; Ultimaps has -11.3%.

### 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. Ultimaps: Freemium. Freemium. The Free plan offers unlimited maps with Excel, CSV, Sheets and Notion imports, 100 address lookups and 20 AI requests per month, and PNG export with a small ultimaps.com credit. Pro (roughly EUR41.58/month billed yearly, around EUR49 monthly) adds unbranded exports, 6x-resolution PNG plus SVG and PDF, unbranded interactive maps, 5,000 lookups and 500 AI requests monthly, and priority support. Custom plans and single-map exports (about EUR12.50 per map) are also offered.

## 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 | [Julius AI](https://openaitools.app/tool/julius-ai) | 665,487 | +5% | Free Trial, Contact for Pricing | Offers powerful AI data analysis and charting from spreadsheets, but lacks dedicated geographic map rendering features. | [.md](https://openaitools.app/tool/julius-ai.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 | [Mappedin](https://openaitools.app/tool/mappedin-com) | 173,962 | -28.6% | Freemium, Contact for Pricing | One live indoor map for wayfinding, operations and security | [.md](https://openaitools.app/tool/mappedin-com.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 | [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) |

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

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