# CleverAI vs Labelbox

CleverAI records 5,439 monthly visits with -2.7% month-over-month growth and Project-based (from $15,000); Contact for Pricing pricing. Labelbox records 762,803 monthly visits with -22.8% growth and Contact for Pricing pricing.

| Metric | [CleverAI](https://openaitools.app/tool/cleverai) | [Labelbox](https://openaitools.app/tool/labelbox) |
| :--- | :--- | :--- |
| Website URL | https://www.cleverai.ai | https://labelbox.com |
| Categories | AI Productivity Tools, AI Assistant, AI Image Generator, AI Search Engine | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools |
| Pricing Model | Project-based (from $15,000); Contact for Pricing | Contact for Pricing |
| Monthly Visits | 5,439 | 762,803 |
| MoM Growth Rate | -2.7% | -22.8% |
| Primary Market | United States | United States |
| Direct Visits | 2,133 | 370,024 |
| Review Score | 4.1 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## CleverAI

CleverAI has evolved from a broad consumer AI toolkit into a product studio that partners with enterprise product and engineering leaders. The company takes a use case from strategy and UX through secure AI engineering and full-stack delivery, working in short, reviewable increments rather than long hand-off phases. Model choice is deliberately flexible: workloads are matched to OpenAI, Anthropic, Gemini, Azure or AWS, and an exit path is preserved so clients are not locked to one vendor.

The typical engagement starts with a Discovery Sprint that de-risks investment before a full build, then a Production Pilot that proves value with real users, data and systems, and finally an Enterprise Product Build for launch with governance, observability and handoff. Recurring themes include private-knowledge copilots with cited answers, workflow automation with audit trails, customer support agents grounded in policy, and adding model-powered features to existing SaaS platforms. CleverAI also builds and operates its own products, including Suitra, an AI-first ERP for small businesses, and Converso, a multi-model chat workspace.

Because deliveries are scoped to each client's stack, pricing is published as engagement starting points rather than a subscription. The business is operated by Azinove SAS and states that security reviews, existing-system integration and production handoff are part of the work rather than an afterthought.

**Pricing & Plans:** Project-based pricing: a Discovery Sprint at $15,000 fixed, a Production Pilot from $45,000, and an Enterprise Product Build from $95,000. Scopes are custom, so final pricing is quoted per engagement.

- **Custom AI agents and copilots:** Purpose-built agents for operations, support and knowledge work, grounded in approved private data with citations.
- **Private-data RAG:** Retrieval systems that respect source permissions and are backed by evaluation rather than demo-only prototypes.
- **Workflow automation:** Human-in-the-loop automations across existing systems with approvals and a complete audit trail.
- **Full-stack SaaS delivery:** Product strategy, UX, AI engineering and production infrastructure built and shipped by one accountable team.
- **Model-agnostic architecture:** Workloads routed across OpenAI, Anthropic, Gemini, Azure and AWS with cost controls and an exit path.

**Strengths:** One accountable team covering product, UX, AI and full-stack engineering; Grounded retrieval and evaluation built in from the start, not bolted on; Model-agnostic design reduces vendor lock-in; Clear fixed and starting price points for each engagement stage

**Limitations:** Project pricing starts in the tens of thousands, so it is not aimed at small budgets; No self-serve product or free tier for hands-on evaluation; Best suited to companies with existing systems and security review processes

[Profile (Markdown)](https://openaitools.app/tool/cleverai.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 CleverAI and Labelbox compare in monthly traffic?

CleverAI has 5,439 monthly visits, while Labelbox has 762,803. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

CleverAI has a month-over-month growth rate of -2.7%; Labelbox has -22.8%.

### How does pricing compare?

CleverAI: Project-based (from $15,000); Contact for Pricing. Project-based pricing: a Discovery Sprint at $15,000 fixed, a Production Pilot from $45,000, and an Enterprise Product Build from $95,000. Scopes are custom, so final pricing is quoted per engagement. 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 | [Base44](https://openaitools.app/tool/base44) | 14,039,232 | +0.5% | Freemium, Paid, Contact for Pricing | Build working apps, websites, and AI agents by describing them | [.md](https://openaitools.app/tool/base44.md) |
| 2 | [Glean](https://openaitools.app/tool/glean) | 3,301,875 | +0.1% | Contact for Pricing | Enterprise AI grounded in your company's own knowledge | [.md](https://openaitools.app/tool/glean.md) |
| 3 | [Abacus.AI](https://openaitools.app/tool/abacus-ai) | 3,278,636 | -1.7% | Contact for Pricing | An all-in-one AI super assistant for professionals and enterprises | [.md](https://openaitools.app/tool/abacus-ai.md) |
| 4 | [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) |
| 5 | [Invisible Technologies](https://openaitools.app/tool/invisible-technologies-inc) | 1,364,520 | +64.4% | Contact for Pricing | Enterprise AI infrastructure where software and expert humans work together | [.md](https://openaitools.app/tool/invisible-technologies-inc.md) |
| 6 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Dust](https://openaitools.app/tool/dust) | 547,217 | +1.8% | Contact for Pricing | Multiplayer AI where people and agents work side by side | [.md](https://openaitools.app/tool/dust.md) |
| 10 | [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) |

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

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