# Dust vs Postel

Dust records 547,217 monthly visits with +1.8% month-over-month growth and Contact for Pricing pricing. Postel records 121,244 monthly visits with +5.8% growth and Free Trial, Paid pricing.

| Metric | [Dust](https://openaitools.app/tool/dust) | [Postel](https://openaitools.app/tool/postel) |
| :--- | :--- | :--- |
| Website URL | https://dust.tt | https://postel.app |
| Categories | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management | AI Tweet Generator, AI Twitter, AI Social Media Post Generator, AI Scheduling |
| Pricing Model | Contact for Pricing | Free Trial, Paid |
| Monthly Visits | 547,217 | 121,244 |
| MoM Growth Rate | +1.8% | +5.8% |
| Primary Market | France | United States |
| Direct Visits | 456,919 | 21,607 |
| Review Score | 4.4 | 4.2 |
| Saved Count | 5 | 1 |
| Supported Platforms | Website | Website |

## Dust

Dust positions itself as 'multiplayer AI' for human-agent collaboration. Rather than giving each employee a private chatbot, it lets teams build agents that have shared access to company knowledge, connected tools, conversations and notifications, so work can move back and forth between people and AI. Agents can be reused across departments, and human review stays part of the loop where it matters.

The platform's differentiator is context. According to Dust, most AI tools can retrieve a single Slack message or CRM record, whereas its agents pull context together across Slack, CRM, documents and other company systems to answer with the full picture and then act on it. Over 70 connectors cover messaging, calendars, CRM, file storage, project management, data and finance tools, and agents can reach MCP servers through the same gateway.

Governance is a first-class feature. Dust offers a dual-layer permission model that separates what agents can access from who can use them, SCIM-synced groups, admin-gated overrides, audit logs and analytics for monitoring adoption, usage, cost and ROI. It is SOC 2 Type II certified, offers US or EU data residency and supports single-tenant deployment. Teams can build agents with 20+ frontier and open-source models from OpenAI, Anthropic, Google, Mistral and others, choosing the right model per workflow. The company says more than 3,000 organizations and 300,000+ agents run on the platform.

**Pricing & Plans:** Contact for pricing. Dust offers a free trial after signup, but its plans are oriented toward teams and enterprises with usage-based credits, volume pricing and dedicated support; you need to talk to sales for exact figures.

- **Agents with company context:** Connect 70+ tools including Slack, Notion, Google Drive, GitHub, Salesforce and Zendesk so agents answer with real company knowledge instead of generic guesses.
- **70+ connectors and MCP support:** Reach messaging, CRM, docs, project management, data, finance and MCP servers through one platform, so agents can act across systems rather than just chat.
- **Model flexibility:** Build agents with 20+ frontier and open-source models from OpenAI, Anthropic, Google and Mistral, and pick the best model for each task.
- **AI-native governance:** A dual-layer permission model, SCIM-synced groups, admin-gated overrides, audit logs and usage analytics keep company data locked down while teams move fast.
- **Multiplayer collaboration:** People and agents share context, tools and notifications, so cross-functional workflows run with reusable skills and human review built in.

**Strengths:** Deep context gathering across 70+ enterprise connectors; Strong enterprise governance with permissions, audit logs and SOC 2 Type II; Model-agnostic: choose among 20+ frontier and open-source models; Shared, reusable agents that scale across departments

**Limitations:** Pricing is sales-led, so costs are hard to estimate before a demo; Setting up connectors and permissions takes real admin work; Best value comes with broad rollout, which is a heavier commitment for small teams

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

## Postel

Postel is built around a single promise: you always have something worth saying, but the blank composer stops you from posting. The tool asks you to drop in what you already have — call notes, an article link, a voice memo, or a podcast you appeared on — and turns that rough material into a set of ready-to-review posts.

The distinguishing feature is voice modeling. Before it writes, Postel reads your past posts and learns how long your lines tend to run, how you typically open, the words you favor, and the phrases you would never use. Drafts are then generated in that learned voice rather than a generic AI register.

The workflow is review-first. Postel drafts a post for each day you publish, places them on a calendar, and lets you keep, edit or skip them one at a time. Kept posts go out on LinkedIn and, once connected, on X, Bluesky and Mastodon. It is aimed at founders, consultants, creators and builders who want consistency without sounding automated.

**Pricing & Plans:** Postel offers a paid subscription with a promotional $1 entry price for the first 7 days, cancelable at any time. Pricing details should be confirmed on the official site.

- **Voice learning:** Reads your historical posts to map line length, opening style, vocabulary and banned phrases so drafts sound like you.
- **Weekly draft engine:** Generates one drafted post for every day you normally publish and slots each into a calendar automatically.
- **Multi-platform scheduling:** Publishes to LinkedIn out of the box and connects X, Bluesky, Mastodon, TikTok and YouTube.
- **Raw input to posts:** Accepts call notes, links, voice memos and podcast recordings as source material for new content.
- **Keep, edit or skip review:** Each draft is presented individually so you stay in control of what actually gets published.

**Strengths:** Learns an individual writing voice rather than producing generic AI text; Covers multiple networks beyond a single platform; Review-first flow keeps a human decision on every post; Turns existing assets like podcasts and notes into published content

**Limitations:** No permanent free tier — only a promotional trial entry price; Full scheduling value depends on connecting several social accounts

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

## Frequently Asked Questions

### How do Dust and Postel compare in monthly traffic?

Dust has 547,217 monthly visits, while Postel has 121,244. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Dust has a month-over-month growth rate of +1.8%; Postel has +5.8%.

### How does pricing compare?

Dust: Contact for Pricing. Contact for pricing. Dust offers a free trial after signup, but its plans are oriented toward teams and enterprises with usage-based credits, volume pricing and dedicated support; you need to talk to sales for exact figures. Postel: Free Trial, Paid. Postel offers a paid subscription with a promotional $1 entry price for the first 7 days, cancelable at any time. Pricing details should be confirmed on the official site.

## 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 | Provides a unified connected workspace for team documents and databases, but lacks Dust's advanced multi-source enterprise knowledge indexing. | [.md](https://openaitools.app/tool/t.md) |
| 2 | [Salesforce Agentforce (formerly Einstein)](https://openaitools.app/tool/salesforce-einstein) | 111,910,743 | +2.2% | Freemium | Integrates deeply with CRM ecosystems to automate enterprise workflows, but is tightly bound to the Salesforce software suite. | [.md](https://openaitools.app/tool/salesforce-einstein.md) |
| 3 | [Glean](https://openaitools.app/tool/glean) | 3,301,875 | +0.1% | Contact for Pricing | Offers robust enterprise-wide permission-aware search and knowledge management, but with less focus on custom multi-model agent workflows. | [.md](https://openaitools.app/tool/glean.md) |
| 4 | [Abacus.AI](https://openaitools.app/tool/abacus-ai) | 3,278,636 | -1.7% | Contact for Pricing | Combines multi-model chat assistants and automated machine learning optimization, but with a heavier focus on data science pipelines. | [.md](https://openaitools.app/tool/abacus-ai.md) |
| 5 | [Taskade](https://openaitools.app/tool/taskade) | 539,714 | -9.4% | Freemium | Turn one prompt into live business apps, AI agents and automated workflows | [.md](https://openaitools.app/tool/taskade.md) |
| 6 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Excels at visual no-code web scraping and data automation pipelines, but lacks Dust's dedicated internal knowledge base architecture. | [.md](https://openaitools.app/tool/gumloop.md) |
| 7 | [Tines](https://openaitools.app/tool/tines) | 273,260 | +24.4% | Freemium, Contact for Pricing | Focuses on secure enterprise workflow automation and security orchestration, but requires more manual setup for custom AI agents. | [.md](https://openaitools.app/tool/tines.md) |
| 8 | [Nuelink](https://openaitools.app/tool/nuelink) | 184,391 | -16% | Free Trial, Paid | Schedule and automate social media on 12 platforms — with AI agents that post for you | [.md](https://openaitools.app/tool/nuelink.md) |
| 9 | [Tweet Hunter](https://openaitools.app/tool/tweet-hunter) | 176,183 | -31% | Paid | Write, schedule, automate and analyse your X growth in one place | [.md](https://openaitools.app/tool/tweet-hunter.md) |
| 10 | [Kore.ai](https://openaitools.app/tool/kore-ai) | 143,328 | -18.2% | Contact for Pricing | Delivers enterprise-grade conversational AI and workflow automation, but focuses more heavily on customer service and enterprise contact centers. | [.md](https://openaitools.app/tool/kore-ai.md) |

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Source: https://openaitools.app/compare/dust-vs-postel

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