# Labelbox vs PublicView

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. PublicView records 148 monthly visits with -53.6% growth and Free Trial pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [PublicView](https://openaitools.app/tool/publicview) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://www.publicview.ai |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI Research Tool, AI For Finance, AI Investing, AI Report Generator |
| Pricing Model | Contact for Pricing | Free Trial |
| Monthly Visits | 762,803 | 148 |
| MoM Growth Rate | -22.8% | -53.6% |
| Primary Market | United States | Global |
| Direct Visits | 370,024 | 57 |
| Review Score | 4.4 | 4.2 |
| 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)

## PublicView

PublicView positions itself as a "public company intelligence platform" built on top of SEC filings. Rather than summarizing documents from model memory, every answer is retrieved from indexed filing excerpts and returned with inline citations you can inspect, so the evidence chain stays attached to the claim. The platform supports three research depths — Quick Mode for fast fact extraction, Deep Mode for entity and relationship mapping, and Track Mode for continuous monitoring — letting users match effort to the question at hand.

Beyond conversational Q&A, PublicView structures filings into other views. A knowledge graph maps companies, people, products, ownership and risk into an explorable network with source-linked connections, a relationships table answers "who is connected to whom and how," and a timeline lays out dated events so you can see how strategy, leadership and risks changed across periods. Watchlists add automatic monitoring: when an 8-K, 10-Q or Form 4 is filed, the platform surfaces an AI-summarized alert so time-sensitive disclosures do not slip past a research cycle. An IPO calendar and lifecycle tracker round out the coverage for companies before and after listing.

The product is aimed at anyone who works from filings: allocators tracking risks and verifying management claims, analysts comparing competitor strategy across 10-Ks and S-1s, lawyers reviewing legal matters across multiple issuers, and journalists hunting for connections when an 8-K drops. PublicView publishes a single flat subscription, and the site explicitly notes that the tool is for research only and does not provide financial advice — outputs are expected to be verified independently.

**Pricing & Plans:** PublicView Pro is a single flat plan at $9.99 USD per month, starting with a 3-day free trial that requires a card and can be canceled anytime. The plan includes SEC-grounded AI chat, deep financials, the knowledge graph, company monitoring and filing alerts, and IPO research, subject to daily limits published on the site (5 Quick analyses, 5 Deep analyses, 50 AI calls, 250k charged tokens and one active analysis).

- **Grounded chat with inline citations:** Ask plain-English questions about 10-Ks, 10-Qs and 8-Ks. The assistant retrieves the relevant filing excerpts and streams an answer with citations you can open to inspect the source text.
- **Visual knowledge graph:** Deep Mode extracts entities and relationships from filings and maps companies, people, products, ownership, strategy and risk into a dual-view network where every node links back to evidence.
- **Relationships table and event timeline:** Search extracted connections to answer who is tied to whom and how, then follow dated events across filing periods to see how leadership, strategy and risks evolved.
- **Filing alerts, watchlists and Form 4 tracking:** Add companies to a watchlist and get AI-summarized notifications when a new 8-K, 10-Q or Form 4 lands, with insider transactions organized for quick review.
- **Multi-company research and IPO coverage:** Compare issuers side by side, work across tickers, CIK numbers or company names, and track IPO research and post-listing lifecycle events in the same workspace.

**Strengths:** Every AI answer is tied to filing excerpts with inline citations you can inspect; Covers the whole loop: Q&A, graph, relationships, timeline and alerts in one workspace; Straightforward single-tier pricing at $9.99/month with a 3-day free trial; Form 4 insider tracking and IPO lifecycle coverage extend it beyond standard filing Q&A

**Limitations:** Published daily caps (5 Quick analyses, 5 Deep analyses, 50 AI calls) can feel tight for heavy research days; Free trial requires a card, so it is not a no-commitment sandbox; It is a research tool only and does not provide financial advice or trade execution

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

## Frequently Asked Questions

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

Labelbox has 762,803 monthly visits, while PublicView has 148. 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%; PublicView has -53.6%.

### 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. PublicView: Free Trial. PublicView Pro is a single flat plan at $9.99 USD per month, starting with a 3-day free trial that requires a card and can be canceled anytime. The plan includes SEC-grounded AI chat, deep financials, the knowledge graph, company monitoring and filing alerts, and IPO research, subject to daily limits published on the site (5 Quick analyses, 5 Deep analyses, 50 AI calls, 250k charged tokens and one active analysis).

## 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 | [MacroMicro](https://openaitools.app/tool/macromicro) | 928,258 | +22.5% | Freemium, Paid | Global macro data and AI research platform for smarter economic decisions | [.md](https://openaitools.app/tool/macromicro.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 | [Intellectia.Ai](https://openaitools.app/tool/intellectia-ai) | 171,347 | +18% | Free Trial, Paid | AI-driven market analysis for faster, data-backed investing decisions | [.md](https://openaitools.app/tool/intellectia-ai.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-publicview

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