# Glean vs OpenCrab

Glean records 3,301,875 monthly visits with +0.1% month-over-month growth and Contact for Pricing pricing. OpenCrab records 0 monthly visits with -100% growth and Freemium pricing.

| Metric | [Glean](https://openaitools.app/tool/glean) | [OpenCrab](https://openaitools.app/tool/opencrab) |
| :--- | :--- | :--- |
| Website URL | https://www.glean.com | https://opencrab.sh |
| Categories | AI Productivity Tools, AI Agent, AI Assistant, AI Search Engine | AI Knowledge Graph, AI Agent, AI Research Tool |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 3,301,875 | 0 |
| MoM Growth Rate | +0.1% | -100% |
| Primary Market | United States | Global |
| Direct Visits | 2,628,666 | 0 |
| Review Score | 4.6 | 4.1 |
| Saved Count | 7 | 0 |
| Supported Platforms | Website | Website |

## Glean

Glean addresses a problem most enterprises hit after their first wave of AI adoption: models are powerful but isolated from the context of the business. The platform builds an enterprise context layer by indexing and understanding content across the tools a company already runs on, then uses that grounding to improve both answer quality and efficiency. Because fewer irrelevant tokens need to be sent to a model, the same question costs less to serve.

The product surface spans four areas: enterprise search, an AI assistant for everyday work, an agent platform for automating long-running processes, and Glean Protect for security and governance. Administrators also get model routing and an AI gateway, letting them decide which models handle which requests without rebuilding integrations. Everything inherits the access permissions of the source systems, so answers stay within each employee's existing rights.

Glean serves large organisations across finance, healthcare, retail, technology, and government, with published customers including Booking.com, Zillow, and Ericsson. It holds SOC 2 Type II, ISO 27001, ISO 42001, HIPAA, GDPR, and TX-RAMP Level 2 attestations, and reports 275+ connectors, 40+ supported language models, and 99.9%+ uptime on core services.

**Pricing & Plans:** Contact for pricing. Glean is licensed to organisations based on seats, connectors, and deployment scope, and is evaluated through a demo rather than self-serve purchase.

- **Permission-aware enterprise search:** Ask a question in plain language and get a cited answer assembled from documents, tickets, wikis, and messages across every connected system, with permissions respected.
- **Agent builder and orchestration:** Reusable agents handle multi-step workflows such as onboarding, account research, or incident follow-up by orchestrating actions across business apps.
- **Model routing and AI gateway:** Glean automatically picks and routes requests to the right model and reasoning level, giving teams access to 40+ LLMs through a single governed gateway.
- **Grounded content and analysis:** Draft on-brand documents, summarise meetings, analyse data, and create content grounded in company context rather than generic model knowledge.
- **Governance and observability:** Administrators get usage controls, spend visibility, audit logging, and compliance-ready governance for every AI interaction.

**Strengths:** Answers cite source systems and inherit their permissions, which removes the main blocker to enterprise-wide rollout; One platform covers search, assistant, and agents instead of three separate vendors; Model routing and token efficiency directly reduce the cost per AI query at scale; 275+ pre-built connectors shorten integration work considerably

**Limitations:** Enterprise pricing is quote-based, so budget planning requires a sales conversation; Full value depends on connecting many internal data sources, which takes IT effort; Smallest teams may find the platform more than they need

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

## OpenCrab

OpenCrab is built around a simple idea: knowledge should be structured as a graph before agents reason over it. You feed the platform documents, URLs, notes or code, and it handles the unglamorous work of parsing, OCR and chunking. From there it extracts entities, concepts, evidence, relationships and claims, weaving them into a source-attributed ontology graph.

The second half of the product is reuse. Graphs can be saved as versioned ontology packs, shared with teammates, or published and sold through the marketplace. A researcher can turn a stack of papers into a queryable, citation-backed graph; a domain expert can package their know-how as a sellable pack; an AI builder can wire the graph into an agent as long-term memory.

The connector layer is what ties it together. A single MCP server means Claude, ChatGPT, Cursor, Codex and other clients all see the same graph, so grounded retrieval travels with you across tools rather than being locked in one workspace. Pricing starts free, with paid tiers for private ingestion and pack publishing.

**Pricing & Plans:** Free tier at $0/month for exploring and sharing public ontology packs and basic graph queries. Pro is $10/month for private document ingestion and a personal graph RAG workspace. Expert is $30/month for pack publishing workflows and MCP reverse ingest. Billing is handled securely via Paddle and can be changed at any time.

- **Document ingestion and parsing:** Upload documents, URLs, notes or code and let the platform handle parsing, OCR and chunking automatically.
- **Ontology graph construction:** Extract entities, concepts, evidence, relationships and claims into a graph where every node traces back to a source.
- **Reusable ontology packs:** Bundle a graph into a versioned, reusable pack you can share with your team or sell in the marketplace.
- **MCP server integration:** One MCP server lets Claude, ChatGPT, Cursor, Codex and other clients query the same graph.
- **Graph RAG querying:** Retrieve grounded, cited answers from your graph instead of relying on a model's memory alone.

**Strengths:** Turns unstructured documents into a source-attributed graph rather than a flat vector index; MCP server means the same grounded knowledge works across Claude, ChatGPT, Cursor and Codex; Ontology packs are reusable, shareable and sellable, creating value beyond a single project; CRUD-style tiers are affordable, with a genuinely usable free level

**Limitations:** Some features (pack publishing, MCP reverse ingest) are gated behind the Expert tier; Best value requires feeding it well-structured documents; messy inputs limit graph quality; The public library and marketplace are still relatively young, so niche ontologies may be sparse

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

## Frequently Asked Questions

### How do Glean and OpenCrab compare in monthly traffic?

Glean has 3,301,875 monthly visits, while OpenCrab has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Glean has a month-over-month growth rate of +0.1%; OpenCrab has -100%.

### How does pricing compare?

Glean: Contact for Pricing. Contact for pricing. Glean is licensed to organisations based on seats, connectors, and deployment scope, and is evaluated through a demo rather than self-serve purchase. OpenCrab: Freemium. Free tier at $0/month for exploring and sharing public ontology packs and basic graph queries. Pro is $10/month for private document ingestion and a personal graph RAG workspace. Expert is $30/month for pack publishing workflows and MCP reverse ingest. Billing is handled securely via Paddle and can be changed at any time.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 2 | [Connected Papers](https://openaitools.app/tool/connected-papers) | 750,576 | +3.1% | Freemium | Explore the academic literature as a visual graph of related papers | [.md](https://openaitools.app/tool/connected-papers.md) |
| 3 | [Dust](https://openaitools.app/tool/dust) | 547,217 | +1.8% | Contact for Pricing | Builds collaborative enterprise AI agents connected to company knowledge, but offers less robust out-of-the-box universal search. | [.md](https://openaitools.app/tool/dust.md) |
| 4 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Turn any document into AI-ready context with agentic parsing and extraction | [.md](https://openaitools.app/tool/llamaindex.md) |
| 5 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Build, share, and control AI agents that actually do the work | [.md](https://openaitools.app/tool/gumloop.md) |
| 6 | [Moveworks](https://openaitools.app/tool/moveworks) | 168,527 | -4.3% | Contact for Pricing | Automates employee IT and HR support requests exceptionally well, but focuses less on general universal document search. | [.md](https://openaitools.app/tool/moveworks.md) |
| 7 | [Kore.ai](https://openaitools.app/tool/kore-ai) | 143,328 | -18.2% | Contact for Pricing | Deploys enterprise conversational assistants and automated workflows, but lacks Glean's unified organization-wide knowledge graph search. | [.md](https://openaitools.app/tool/kore-ai.md) |
| 8 | [Coworker AI](https://openaitools.app/tool/coworker-ai) | 129,346 | -1.8% | Free Trial, Paid, Contact for Pricing | Creates permission-aware context graphs and routes tasks across enterprise tools, but has a smaller connector library than Glean. | [.md](https://openaitools.app/tool/coworker-ai.md) |
| 9 | [Sana](https://openaitools.app/tool/sana-labs) | 109,714 | -25.5% | Paid, Contact for Pricing | Combines enterprise search, AI agents, and corporate learning, but is less specialized for pure universal workplace search than Glean. | [.md](https://openaitools.app/tool/sana-labs.md) |
| 10 | [Open Knowledge Maps](https://openaitools.app/tool/openknowledgemaps-org) | 83,432 | -2.4% | Free | AI-powered visual discovery of scientific knowledge | [.md](https://openaitools.app/tool/openknowledgemaps-org.md) |

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Source: https://openaitools.app/compare/glean-vs-opencrab

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