# Eigent AI vs Fact0

Eigent AI records 575,703 monthly visits with +1.4% month-over-month growth and Freemium, Free Trial, Contact for Pricing pricing. Fact0 records 0 monthly visits with 0% growth and Open Source (MIT); self-hosted, no subscription fees pricing.

| Metric | [Eigent AI](https://openaitools.app/tool/eigent-ai) | [Fact0](https://openaitools.app/tool/fact0) |
| :--- | :--- | :--- |
| Website URL | https://www.eigent.ai | https://fact0.io |
| Categories | AI Agent, AI Workflow, AI Productivity Tools, AI Browsers | AI Agent |
| Pricing Model | Freemium, Free Trial, Contact for Pricing | Open Source (MIT); self-hosted, no subscription fees |
| Monthly Visits | 575,703 | 0 |
| MoM Growth Rate | +1.4% | 0% |
| Primary Market | United States | Global |
| Direct Visits | 83,414 | 0 |
| Review Score | 4.4 | 4.5 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Eigent AI

Eigent positions itself as an open-source "Cowork Desktop" — a multi-agent workforce that lives on your machine rather than a closed cloud SaaS. In a session you give plain-language instructions, and a coordinating agent decomposes the work, dispatches specialist agents (browser, terminal, document, research), and streams a visible trajectory of searches, page reads, extractions, and file writes. Output is produced as real artifacts — Markdown briefs, CSVs, charts, HTML — alongside the reasoning trace, so you can inspect sources and compare revisions before accepting the result.

The product leans heavily on control and deployability. Execution can run locally or be self-hosted on infrastructure your team owns; secret handling and permission decisions stay bound locally. Agents can be paused for approvals on sensitive steps and asked questions even after an interruption, and an "Agent browser" restricts which targets agents may touch. Model selection is flexible: cloud providers, enterprise gateways, local models, and BYOK, switchable without rebuilding a workflow.

Eigent also introduces reusable "Spaces" that package agents, Skills, connectors, and instructions so a team sets up a working environment once and reuses it. Automation can be triggered on a schedule, event, or condition, and remote control lets you check progress through the browser or channels like WhatsApp. The project is developed in the open, with a share of subscription revenue going back to the CAMEL-AI open-source community.

**Pricing & Plans:** Freemium plus paid tiers. The Free plan provides the open-source desktop app with BYOK and local models at $0. The Plus plan is listed at $19.99/month with 2,000 monthly task credits and a 7-day free trial, and Pro at $99.99/month with 10,000 monthly credits and priority support. A Teams plan with central billing and shared libraries is marked coming soon, and Enterprise is custom-quoted with local deployment, security controls, and an agent RL environment. The fully open-source build can also be self-hosted for free.

- **Multi-agent cowork workforce:** A coordinating agent breaks a goal into steps and dispatches specialist browser, terminal, document, and research agents that work in parallel inside a local workspace.
- **Open source and self-hostable:** The desktop app is open source and can run locally or be self-hosted on your own infrastructure with your own keys, so data and secrets stay under your control.
- **Model agnostic, BYOK:** Connect cloud providers, enterprise gateways, or local models and switch between them without rebuilding workflows; use your own API keys or free local models.
- **Traceable results and approvals:** Follow each agent's searches, sources, and file changes, compare versions, then approve, revise, or ask a follow-up before accepting output.
- **Spaces, Skills, and automations:** Package reusable agent setups, Skills, and connectors into Spaces, and trigger work on a schedule, event, or condition with remote progress checks.

**Strengths:** Open source with a free self-hosted path and BYOK, avoiding vendor lock-in; Genuine multi-agent orchestration with visible reasoning and sources; Strong deployment flexibility: local, self-hosted, or enterprise; Reusable Spaces and automations reduce repeated setup work

**Limitations:** Requires some technical comfort to install, configure models, and manage permissions; Paid tiers are credit-metered, so heavy use needs cost monitoring; Some advertised team features are still marked coming soon

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

## 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)

## Frequently Asked Questions

### How do Eigent AI and Fact0 compare in monthly traffic?

Eigent AI has 575,703 monthly visits, while Fact0 has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Eigent AI has a month-over-month growth rate of +1.4%; Fact0 has 0%.

### How does pricing compare?

Eigent AI: Freemium, Free Trial, Contact for Pricing. Freemium plus paid tiers. The Free plan provides the open-source desktop app with BYOK and local models at $0. The Plus plan is listed at $19.99/month with 2,000 monthly task credits and a 7-day free trial, and Pro at $99.99/month with 10,000 monthly credits and priority support. A Teams plan with central billing and shared libraries is marked coming soon, and Enterprise is custom-quoted with local deployment, security controls, and an agent RL environment. The fully open-source build can also be self-hosted for free. 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.

## 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 | [Manus](https://openaitools.app/tool/manus) | 19,195,779 | -1.7% | Free Trial | Executes complex autonomous multi-step goals and browser tasks, but operates as a cloud service rather than open-source desktop software. | [.md](https://openaitools.app/tool/manus.md) |
| 3 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation platform with integrated AI agent nodes, but lacks Eigent's native desktop terminal and file manipulation. | [.md](https://openaitools.app/tool/n8n.md) |
| 4 | [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) |
| 5 | [WorkBuddy](https://openaitools.app/tool/workbuddy) | 2,341,262 | +43.9% | Freemium | Desktop AI workspace that turns task briefs into completed office deliverables, but lacks open-source transparency. | [.md](https://openaitools.app/tool/workbuddy.md) |
| 6 | [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) |
| 7 | [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) |
| 8 | [Taskade](https://openaitools.app/tool/taskade) | 539,714 | -9.4% | Freemium | Generates business apps and automated agents from text prompts, but functions primarily as a collaborative cloud workspace. | [.md](https://openaitools.app/tool/taskade.md) |
| 9 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Visual no-code AI agent builder for web and data workflows, but executes in the cloud rather than local desktop. | [.md](https://openaitools.app/tool/gumloop.md) |
| 10 | [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) |

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Source: https://openaitools.app/compare/eigent-ai-vs-fact0

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