# Fact0 vs Glean

Fact0 records 0 monthly visits with 0% month-over-month growth and Open Source (MIT); self-hosted, no subscription fees pricing. Glean records 3,301,875 monthly visits with +0.1% growth and Contact for Pricing pricing.

| Metric | [Fact0](https://openaitools.app/tool/fact0) | [Glean](https://openaitools.app/tool/glean) |
| :--- | :--- | :--- |
| Website URL | https://fact0.io | https://www.glean.com |
| Categories | AI Agent | AI Productivity Tools, AI Agent, AI Assistant, AI Search Engine |
| Pricing Model | Open Source (MIT); self-hosted, no subscription fees | Contact for Pricing |
| Monthly Visits | 0 | 3,301,875 |
| MoM Growth Rate | 0% | +0.1% |
| Primary Market | Global | United States |
| Direct Visits | 0 | 2,628,666 |
| Review Score | 4.5 | 4.6 |
| Saved Count | 0 | 7 |
| Supported Platforms | Website | Website |

## Fact0

Fact0 addresses a practical gap in agent engineering: once an AI agent runs autonomously, it is hard to say precisely what it did. Fact0 installs locally via Docker Compose (a Go API, a Next.js dashboard and PostgreSQL) and creates one owner and one workspace without any cloud account. You then instrument your agent through the Python SDK or connect the Claude Code plugin, and every supported span — prompts, tool calls, tool results, assistant text, handled failures — is written to your own database.

Inspection is a first-class feature. A graph view shows the path through a run, a timing waterfall shows ordering, and each recorded step exposes the captured value beside it so you can expand, copy or download the raw content. Replay reconstructs saved execution events at your own pace; importantly, replay replays the record and does not re-run the agent, so you are always looking at what genuinely happened.

Fact0 is deliberately honest about its limits. It is experimental software under best-effort maintenance, with one owner and one workspace in the current release. Audit verification proves that the checked records are consistent with their hashes and preceding links, and export verification checks signed file bytes against a separately trusted public key — but neither proves complete capture, truthful source data or protection from an administrator replacing the whole history. Missing or unsupported content is marked partial or unavailable rather than silently omitted.

**Pricing & Plans:** Free and open source under the MIT license. You self-host with Docker Compose, so there are no Fact0 subscription fees or per-seat pricing; you only bear your own infrastructure costs. There is no hosted billing or team-invitation offering, and no SLA.

- **Local-first capture:** Run the API, dashboard and PostgreSQL in your own environment via Docker Compose, then point your agent at the local instance with an API key. Data and signing keys stay with your installation.
- **Two entry points, one history:** Record Python agents through the SDK (execution spans, tool results, supported model content, audit events) and Claude Code sessions through the collector plugin, then inspect both in the same workspace.
- **Execution graphs and replay:** Follow a run through a graph, a timing waterfall and recorded spans, then step through saved events at your own pace. Replay reconstructs the record without re-running the agent.
- **Hash-chained audit records:** Check the consistency of stored events against their hashes and preceding links, with capture gaps reported visibly rather than hidden.
- **Signed evidence exports:** Download authenticated PDF reports and evidence ZIPs, and verify the signed PDF and verification JSON against a separately trusted instance public key.

**Strengths:** Open source under the MIT license and fully self-hosted, so sensitive prompts and source code never leave your infrastructure; Unusually transparent documentation that states capture limitations and what audit verification actually proves; Docker Compose setup with a one-owner, one-workspace model makes getting started quick and scriptable; Covers both Python agents and Claude Code in a single inspection workspace

**Limitations:** Explicitly experimental with best-effort maintenance, so it is not suited to production-critical reliance; Not a hosted service: no cloud account, no team invitations, no SLA, and none of the operational support a managed product provides; Capture completeness depends entirely on your instrumentation and supported hooks; absent content is only marked partial or unavailable

[Profile (Markdown)](https://openaitools.app/tool/fact0.md)

## 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)

## Frequently Asked Questions

### How do Fact0 and Glean compare in monthly traffic?

Fact0 has 0 monthly visits, while Glean has 3,301,875. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Fact0 has a month-over-month growth rate of 0%; Glean has +0.1%.

### How does pricing compare?

Fact0: Open Source (MIT); self-hosted, no subscription fees. Free and open source under the MIT license. You self-host with Docker Compose, so there are no Fact0 subscription fees or per-seat pricing; you only bear your own infrastructure costs. There is no hosted billing or team-invitation offering, and no SLA. 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.

## 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 | [Hermes-Agent](https://openaitools.app/tool/hermes-agent-1) | 3,638,741 | -5.4% | Freemium | A free, open-source personal AI agent that learns your projects and works across every messaging app. | [.md](https://openaitools.app/tool/hermes-agent-1.md) |
| 3 | [Clawdbot (OpenClaw)](https://openaitools.app/tool/clawdbot) | 1,903,068 | -25.4% | Paid, Free | Open-source personal AI assistant that runs on your own machine and works from chat apps | [.md](https://openaitools.app/tool/clawdbot.md) |
| 4 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder for custom AI agents and workflows | [.md](https://openaitools.app/tool/mindstudio.md) |
| 5 | [Eigent AI](https://openaitools.app/tool/eigent-ai) | 575,703 | +1.4% | Freemium, Free Trial, Contact for Pricing | Open-source desktop AI workforce that runs browser, file, and app tasks for you | [.md](https://openaitools.app/tool/eigent-ai.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 | [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) |
| 8 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.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) |

---
Source: https://openaitools.app/compare/fact0-vs-glean

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)