# dassi vs Eigent AI

dassi records 12,194 monthly visits with +57.9% month-over-month growth and Freemium pricing. Eigent AI records 575,703 monthly visits with +1.4% growth and Freemium, Free Trial, Contact for Pricing pricing.

| Metric | [dassi](https://openaitools.app/tool/dassi) | [Eigent AI](https://openaitools.app/tool/eigent-ai) |
| :--- | :--- | :--- |
| Website URL | https://dassi.ai | https://www.eigent.ai |
| Categories | AI Agent, AI Workflow, AI Browsers, AI Productivity Tools | AI Agent, AI Workflow, AI Productivity Tools, AI Browsers |
| Pricing Model | Freemium | Freemium, Free Trial, Contact for Pricing |
| Monthly Visits | 12,194 | 575,703 |
| MoM Growth Rate | +57.9% | +1.4% |
| Primary Market | India | United States |
| Direct Visits | 7,443 | 83,414 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## dassi

dassi installs as a side panel in Chrome, Edge, or Brave, so it uses tabs you are already signed into rather than a fresh browser or an API integration. Teaching it is deliberately manual the first time: you either describe the job in plain English or demonstrate it while dassi watches and reads the pages itself. From there you set the constraints — which sites it may touch, what varies each run, when it fires, where output goes, and which steps must be confirmed by you before they happen. Runs happen locally on your machine, which means your browser needs to be open when a scheduled run comes due.

The product's real argument is cost discipline on repeat work. dassi keeps each job's context byte-stable inside a run so repeated steps read from your model provider's prompt cache, cutting input token spend substantially on models that support caching. As it works a site, it also writes itself a small JavaScript helper library for that site, so later runs call a function instead of re-deriving selectors from screenshots and HTML each time. Corrections you make are stored in an editable memory that carries into future runs instead of being lost with the chat.

You choose the engine: Claude, GPT, Gemini, Grok, DeepSeek, Kimi, or another OpenRouter model, with your own key or included credits, switchable at any time. Typical shapes of work are reconciliation (matching payouts to orders), screening (scoring applicants into an ATS), and reporting (assembling a weekly dashboard into your own template). When a run hits something ambiguous, dassi stops and asks — in the side panel, or over Telegram if you are away from your desk.

**Pricing & Plans:** Currently in beta with free credits that do not expire and no credit card required to start. Model usage can be billed through your own provider API key or through dassi's included credits. A separate Enterprise offering is available for teams; check the pricing page for current tiers and credit rates.

- **Teach-once workflows:** Describe a job in plain English or demonstrate it once; dassi saves it as a named workflow with a plan, sites, inputs, and a run history.
- **Scheduled or on-demand runs:** Trigger a workflow manually or let its schedule fire, receiving a completion notice or an exception that only you can decide.
- **Human approval gates:** Flag the steps that must be confirmed — sending an email, opening a support case, rejecting a candidate — and approve from the side panel or Telegram.
- **Editable task memory:** Corrections you give about a supplier, column, or tone are written into a memory you can read and edit, so they apply to the next run.
- **Token and site-skill efficiency:** Byte-stable context enables provider prompt caching for large input savings, while learned per-site JavaScript libraries replace repeated DOM re-derivation.

**Strengths:** Runs in the browser you already have, on accounts you are already signed into, with no integrations to wire up; Model-agnostic: bring Claude, GPT, Gemini, or any OpenRouter model with your own key; Caching and learned site skills make repeated jobs progressively cheaper than a fresh chat each time; Explicit approval checkpoints plus local execution keep credentials out of the agent's hands

**Limitations:** Scheduled runs require your browser to be open and the machine awake at the trigger time; You must teach each job before it becomes reliable, so the first run is a real time investment; Currently labeled beta, so feature surface and credit pricing may still shift

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

## 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)

## Frequently Asked Questions

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

dassi has 12,194 monthly visits, while Eigent AI has 575,703. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

dassi has a month-over-month growth rate of +57.9%; Eigent AI has +1.4%.

### How does pricing compare?

dassi: Freemium. Currently in beta with free credits that do not expire and no credit card required to start. Model usage can be billed through your own provider API key or through dassi's included credits. A separate Enterprise offering is available for teams; check the pricing page for current tiers and credit rates. 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.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Muse](https://openaitools.app/tool/muse-ai-1) | 45,751,822 | +228.3% | Contact for Pricing | Your personal AI agent from Meta that actually gets things done | [.md](https://openaitools.app/tool/muse-ai-1.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 | [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) |
| 5 | [Clawdbot (OpenClaw)](https://openaitools.app/tool/clawdbot) | 1,903,068 | -25.4% | Paid, Free | Open-source personal AI assistant running locally, but focuses more on messaging integrations than heavy terminal orchestration. | [.md](https://openaitools.app/tool/clawdbot.md) |
| 6 | [Dia Browser](https://openaitools.app/tool/dia-browser) | 1,254,172 | +108.4% | Free | The AI browser that reads between your tabs | [.md](https://openaitools.app/tool/dia-browser.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | No-code platform for building specialist multi-agent workforces, but lacks local desktop execution capabilities. | [.md](https://openaitools.app/tool/relevance-ai.md) |
| 10 | [OpenBot](https://openaitools.app/tool/openbot) | 145,308 | +2,617.1% | Freemium, Free, Contact for Pricing | Runs local collaborative teams of AI agents on your desktop, but features a less mature developer ecosystem than Eigent. | [.md](https://openaitools.app/tool/openbot.md) |

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

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