# Dust vs NOAN

Dust records 547,217 monthly visits with +1.8% month-over-month growth and Contact for Pricing pricing. NOAN records 3,663 monthly visits with -15.7% growth and Paid pricing.

| Metric | [Dust](https://openaitools.app/tool/dust) | [NOAN](https://openaitools.app/tool/noan) |
| :--- | :--- | :--- |
| Website URL | https://dust.tt | https://getnoan.com |
| Categories | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management | AI Assistant, AI Knowledge Management, Large Language Models (LLMs), AI Marketing |
| Pricing Model | Contact for Pricing | Paid |
| Monthly Visits | 547,217 | 3,663 |
| MoM Growth Rate | +1.8% | -15.7% |
| Primary Market | France | United States |
| Direct Visits | 456,919 | 1,450 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 5 | 0 |
| 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)

## NOAN

NOAN describes itself as fact infrastructure for agentic companies. The problem it addresses is a familiar one for teams running AI agents: the price lives in fourteen system prompts, three of which are wrong; retrieval surfaces last year's deck next to this year's; memory recalls what someone said on a call rather than what was decided. NOAN's answer is to keep your company's verified facts in one place and have every agent, app, and site read them live from a single API.

Technically, NOAN exposes a plain REST API over api.getnoan.com/v1 and an MCP server at mcp.getnoan.com/mcp. You create a project, then issue a key for each agent, app, or site, scoped to the stacks it needs. A single GET returns the latest verified version of a fact block, along with who verified it and its sources. Agents can write back, posting new versions that supersede the previous ones while keeping the lineage — and if review-on-write is enabled, those writes wait for a person to approve them before anything can read them. Around that core, NOAN handles the surrounding mechanics: classification, permissions, partner sharing, and per-key activity auditing.

The platform also ships the workspace pieces agents need day to day — a shared task board for people and agents, contacts with history and open work, notes linked to facts, and reusable assets and templates. It integrates with Claude, ChatGPT, Cursor, and other MCP clients, and supports multiple model providers because the model is a configuration choice. Beyond the tooling, NOAN publishes a startup program and grant, plus material for agencies that want to run a separate fact base per client.

**Pricing & Plans:** Paid, with a free starting point: you can start free and scale when you ship, and pricing is presented as live/usage-based in the app. API access, MCP, versioned facts, review-on-write, and scoped keys are part of the platform, with higher tiers aimed at teams and agencies running the facts layer in production. A startup program and grant are also offered.

- **Verified, versioned facts:** Each fact keeps its date, sources, and the person who verified it, so nothing is silently overwritten and agents can show the receipt behind an answer.
- **Scoped keys and permissions:** Scope one key per agent, app, or site and limit it to the stacks it needs, so the right keys read the right facts and nothing else.
- **Review on write:** Turn review on for a project or a single key so any write an agent proposes waits for a human to verify it before it can be read.
- **Time Travel:** See your entire fact base as it stood on any past date, so you can answer what was true when a decision was made.
- **Activity on the record:** Every agent action lands on one timeline, marked by the key that made it, giving you auditability across agents, apps, and sites.

**Strengths:** Solves a real and specific agent problem — grounding — instead of adding another generic chatbot; Version history, sources, and named verification make outputs auditable and defensible; Model-agnostic and accessible over both REST and MCP, so it fits many stacks; Review-on-write lets agents propose updates without letting them silently change pricing or policy

**Limitations:** The product is a new category (fact infrastructure), so new users need to absorb unfamiliar concepts before they see value; Value depends on teams actually maintaining facts, so adoption requires some process discipline; Pricing is presented as dynamic and depends on the scale you ship at; It complements rather than replaces memory or RAG layers, so it is another integration to wire up

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

## Frequently Asked Questions

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

Dust has 547,217 monthly visits, while NOAN has 3,663. 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%; NOAN has -15.7%.

### 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. NOAN: Paid. Paid, with a free starting point: you can start free and scale when you ship, and pricing is presented as live/usage-based in the app. API access, MCP, versioned facts, review-on-write, and scoped keys are part of the platform, with higher tiers aimed at teams and agencies running the facts layer in production. A startup program and grant are also offered.

## 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 | [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 | Enterprise AI grounded in your company's own knowledge | [.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 | [Exa](https://openaitools.app/tool/exa-ai) | 1,062,574 | +16.8% | Freemium, Contact for Pricing | Web search API and crawler built for AI agents | [.md](https://openaitools.app/tool/exa-ai.md) |
| 6 | [You.com](https://openaitools.app/tool/you) | 948,349 | +7% | Freemium | Search and inference APIs that give AI models real-time web data | [.md](https://openaitools.app/tool/you.md) |
| 7 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | The data, evaluations and systems behind AI that has to be right. | [.md](https://openaitools.app/tool/scale.md) |
| 8 | [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) |
| 9 | [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) |
| 10 | [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) |

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

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