# Glean vs Iris.ai

Glean records 3,301,875 monthly visits with +0.1% month-over-month growth and Contact for Pricing pricing. Iris.ai records 22,006 monthly visits with -27.9% growth and Contact for Pricing pricing.

| Metric | [Glean](https://openaitools.app/tool/glean) | [Iris.ai](https://openaitools.app/tool/iris-ai) |
| :--- | :--- | :--- |
| Website URL | https://www.glean.com | https://iris.ai |
| Categories | AI Productivity Tools, AI Agent, AI Assistant, AI Search Engine | AI Knowledge Management, AI Research Tool, AI Summarizer, AI Chatbot |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 3,301,875 | 22,006 |
| MoM Growth Rate | +0.1% | -27.9% |
| Primary Market | United States | India |
| Direct Visits | 2,628,666 | 8,758 |
| Review Score | 4.6 | 4.3 |
| Saved Count | 7 | 4 |
| 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)

## Iris.ai

Iris.ai addresses a specific problem in enterprise AI: in fields where a wrong answer carries real cost, it is not enough for a language model to be fluent. The platform acts as a harness around the model, defining which documents and data sources it is allowed to read, and recording how each answer was assembled so results can be audited and reproduced rather than trusted on faith.

The company has been working on scientific text understanding for around a decade and applies that experience to technical literature, patents, internal reports and structured enterprise systems. The product line is organized around three entry points: Axion for converting unstructured data into AI-ready intelligence, Neuralith for building a knowledge engine over enterprise content, and RSpace for precision intelligence in complex research and development workflows.

Iris.ai sells to organizations rather than individuals, so entry is through a demo request and pricing is quoted per engagement. Documentation, help center articles, case studies and webinar resources are published on the site for evaluation before contact. It remains an actively developed commercial platform rather than a downloadable consumer app.

**Pricing & Plans:** Contact for pricing. Iris.ai sells to enterprises and R&D organizations through a demo request and tailored quotations rather than published self-serve plans; there is no listed free tier.

- **Model grounding and control:** Defines which documents and internal sources a language model may read, restricting answers to approved material.
- **Step-by-step answer tracing:** Measures and records how an answer was assembled so outputs can be audited and reproduced.
- **Scientific text understanding:** Applies a decade of NLP work on technical literature and patents to interpret dense scientific language.
- **Data-to-AI pipelines:** Turns unstructured documents and enterprise data into structured, AI-ready intelligence.
- **R&D knowledge engines:** Builds searchable knowledge layers over internal repositories for research and engineering teams.

**Strengths:** Purpose-built for high-stakes domains where wrong answers are costly; Controlled model grounding with source restrictions; Traceable, reproducible answers suited to audit and review; Roughly a decade of scientific text understanding experience

**Limitations:** No published self-serve pricing or free tier; Onboarding requires a demo request and sales process; Aimed at organizations with substantial document corpora, not individual users

[Profile (Markdown)](https://openaitools.app/tool/iris-ai.md)

## Frequently Asked Questions

### How do Glean and Iris.ai compare in monthly traffic?

Glean has 3,301,875 monthly visits, while Iris.ai has 22,006. 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%; Iris.ai has -27.9%.

### 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. Iris.ai: Contact for Pricing. Contact for pricing. Iris.ai sells to enterprises and R&D organizations through a demo request and tailored quotations rather than published self-serve plans; there is no listed free tier.

## 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 | [Kimi AI](https://openaitools.app/tool/kimi-chat) | 19,632,261 | -23.4% | Free | Moonshot AI's long-context assistant for research, coding, and agentic work | [.md](https://openaitools.app/tool/kimi-chat.md) |
| 3 | [Consensus](https://openaitools.app/tool/consensus) | 6,014,388 | -1.2% | Freemium | AI academic search engine for peer-reviewed science | [.md](https://openaitools.app/tool/consensus.md) |
| 4 | [Harvey](https://openaitools.app/tool/harvey-ai) | 1,832,998 | +26.1% | Contact for Pricing | Domain-specific AI for law firms, in-house legal teams, and professional services | [.md](https://openaitools.app/tool/harvey-ai.md) |
| 5 | [Elicit](https://openaitools.app/tool/elicit) | 1,751,507 | +3.1% | Freemium | AI research assistant for evidence-based literature review and synthesis | [.md](https://openaitools.app/tool/elicit.md) |
| 6 | [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) |
| 7 | [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) |
| 8 | [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) |
| 9 | [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) |
| 10 | [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) |

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Source: https://openaitools.app/compare/glean-vs-iris-ai

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