# Glean vs Select Star

Glean records 3,301,875 monthly visits with +0.1% month-over-month growth and Contact for Pricing pricing. Select Star records 0 monthly visits with — growth and Contact for Pricing pricing.

| Metric | [Glean](https://openaitools.app/tool/glean) | [Select Star](https://openaitools.app/tool/select-star) |
| :--- | :--- | :--- |
| Website URL | https://www.glean.com | https://chromewebstore.google.com/detail/select-star/okjjmjmiaemccchgkpchjpkaomabndek |
| Categories | AI Productivity Tools, AI Agent, AI Assistant, AI Search Engine | Other |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 3,301,875 | 0 |
| MoM Growth Rate | +0.1% | — |
| Primary Market | United States | Global |
| Direct Visits | 2,628,666 | 0 |
| Review Score | 4.6 | 4.4 |
| Saved Count | 7 | 1 |
| Supported Platforms | Website | Browser Extension |

## 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)

## Select Star

Select Star attacks a problem every maturing data team recognizes: the data exists, but nobody is sure which version of it is authoritative or who to ask. The platform connects to your warehouses, ELT/ETL pipelines, and BI tools, reads their metadata and query history, and automatically produces documentation, lineage, and usage statistics. Instead of a manually maintained spreadsheet of tables, you get a living catalog that reflects what is actually being queried, including which tables have quietly gone unused.

Lineage is the centerpiece. Select Star traces data down to the column level and across platforms, so you can answer concrete questions: if this field changes, which dashboards break, and who gets affected? The same graph is used for governance — PII tags can be propagated to downstream columns so sensitive data is visible wherever it flows, which matters for audits and compliance work. A data portal layer sits on top, letting anyone search for certified datasets, read descriptions and tags, and record discussions against a dataset so answers stay attached to the data.

More recently Select Star has leaned into AI readiness. Reporting is that it is now part of Snowflake, and the product exposes metadata, lineage, and generated semantic models to LLMs and agents through interfaces such as an MCP server, aiming to be the context layer that makes AI answers trustworthy rather than plausible. Pricing is quote-based rather than published, and is typically sized against the number of connected sources, data volume, and required seats, so evaluation starts with a sales conversation.

**Pricing & Plans:** Quote-based enterprise pricing; Select Star does not publish public list prices. Cost depends on the scale of your environment — connected data sources, data volume, and the seats or capabilities you need — so evaluation typically starts with contacting sales. There is a free Chrome extension, and the SEO/AI discovery scoop of legacy listings should not be read as a price.

- **Automated data catalog and documentation:** Select Star automatically indexes metadata across warehouses, pipelines, and BI tools, generating documentation so analysts spend less time hunting for the right dataset.
- **Column-level lineage and impact analysis:** Cross-platform, column-level lineage shows where data originates, who is using it, and which dashboards are built on top of it, so impact is visible before you change anything.
- **Data portal for shared knowledge:** A shared data portal where teams tag and describe assets, ask questions, and browse previous discussions attached to each dataset, turning tribal knowledge into searchable documentation.
- **Governance, PII tracking, and security:** Use lineage and tagging to locate exactly where sensitive fields travel, propagate PII tags downstream, and support SOC 2-aligned security, confidentiality, and availability practices.
- **AI-ready metadata for LLMs and agents:** Reverse-engineered semantic models and an MCP server expose metadata, lineage, and semantics to LLMs and agents, giving AI tools the context they need for reliable answers.

**Strengths:** Automated cataloging removes the manual work of maintaining a data inventory; Column-level, cross-platform lineage makes change impact analysis concrete; PII tag propagation and SOC 2-aligned controls support governance and audits; A shared portal turns scattered tribal knowledge into searchable documentation

**Limitations:** Enterprise-focused pricing means no transparent public price list and a longer procurement cycle; Value depends heavily on how many data sources and BI tools you connect; a small stack gains less; Heavier governance and tagging features can require ongoing admin effort to keep metadata useful; Being acquired by Snowflake may raise questions about roadmap focus for non-Snowflake-centric stacks

[Profile (Markdown)](https://openaitools.app/tool/select-star.md)

## Frequently Asked Questions

### How do Glean and Select Star compare in monthly traffic?

Glean has 3,301,875 monthly visits, while Select Star 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%; Select Star has —.

### 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. Select Star: Contact for Pricing. Quote-based enterprise pricing; Select Star does not publish public list prices. Cost depends on the scale of your environment — connected data sources, data volume, and the seats or capabilities you need — so evaluation typically starts with contacting sales. There is a free Chrome extension, and the SEO/AI discovery scoop of legacy listings should not be read as a price.

## 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 | [Duck.ai](https://openaitools.app/tool/duck-ai) | 26,431,539 | +10.7% | Free | Private AI chat from the makers of DuckDuckGo | [.md](https://openaitools.app/tool/duck-ai.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 | [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) |
| 5 | [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) |
| 6 | [Dex — Personal CRM & LinkedIn Assistant](https://openaitools.app/tool/linkedin-gpt-assistant-by-dex) | 156,354 | +1.6% | Paid | The personal CRM that keeps your network warm — with your LinkedIn graph baked in | [.md](https://openaitools.app/tool/linkedin-gpt-assistant-by-dex.md) |
| 7 | [Defined.ai](https://openaitools.app/tool/definedcrowd-com) | 146,251 | -21% | Contact for Pricing | Enterprise AI training data, annotation and evaluation services | [.md](https://openaitools.app/tool/definedcrowd-com.md) |
| 8 | [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) |
| 9 | [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) |
| 10 | [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) |

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Source: https://openaitools.app/compare/glean-vs-select-star

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