# Dust vs QA.tech

Dust records 547,217 monthly visits with +1.8% month-over-month growth and Contact for Pricing pricing. QA.tech records 30,550 monthly visits with -4.4% growth and Paid, Contact for Pricing pricing.

| Metric | [Dust](https://openaitools.app/tool/dust) | [QA.tech](https://openaitools.app/tool/qa-tech) |
| :--- | :--- | :--- |
| Website URL | https://dust.tt | https://qa.tech |
| Categories | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management | AI Testing, AI Agent, AI Developer Tools, AI Productivity Tools |
| Pricing Model | Contact for Pricing | Paid, Contact for Pricing |
| Monthly Visits | 547,217 | 30,550 |
| MoM Growth Rate | +1.8% | -4.4% |
| Primary Market | France | Sweden |
| Direct Visits | 456,919 | 21,231 |
| Review Score | 4.4 | 4.3 |
| 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)

## QA.tech

QA.tech positions itself as the verification layer for teams shipping software with heavy AI assistance: coding got much faster, but review and QA did not keep pace. Instead of maintaining a fragile library of selectors and scripts, QA.tech runs autonomous agents that open your live web or native mobile app, work toward goals the way a person would, and report back on what actually works before code is merged.,The product is built around continuous, dynamic testing rather than one-off suites. Connect GitHub, GitLab or Bitbucket and a CI provider, and agents automatically pick up each pull request together with its preview environment, run end-to-end and exploratory passes, and comment on the PR with results. When something fails, you get screenshots, console and network activity and the agent's reasoning at the point of failure, which shortens time to root cause considerably.,Testing is also context-aware over time. Journeys and domain rules you spell out in chat accumulate as knowledge the agents reuse on every later run, and a blast-radius view flags changes that ship untested because a required test user or journey is missing. The platform is cloud-native, needs no code access, and is targeted at QA leads, engineers, CTOs and DevOps teams; Vercel Ventures and founder investors back the company. Pricing is not published as a simple self-serve number — teams book a demo, though a free getting-started path is offered.

**Pricing & Plans:** Enterprise-style, contact-for-pricing model: the site offers a free getting-started path and a demo booking rather than public per-seat numbers, so exact costs depend on team size, coverage scope and mobile testing needs.

- **Plain-language test authoring:** Describe a journey or rule in chat and the agent turns it into durable test cases that survive refactors and redesigns.
- **PR-level verification:** Every pull request gets a dynamic exploratory pass with preview environments, failure breakdowns, screenshots, console and network logs.
- **Web and native mobile:** Agents target real browsers and native iOS and Android apps, so coverage reaches beyond the web front end.
- **CI, Git and issue-tracker integrations:** Findings flow into Jira and Linear, and agents can be queried over MCP by other coding agents.
- **Blast-radius analysis:** Detects when changes to a module are untested and recommends the exact journeys or test users needed to close the gap.

**Strengths:** Agents test visually without selectors, so suites survive redesigns and framework migrations; Runs automatically on every pull request with preview environments; Plain-English test authoring is accessible to non-engineers; Rich failure evidence — screenshots, logs, network data and agent reasoning

[Profile (Markdown)](https://openaitools.app/tool/qa-tech.md)

## Frequently Asked Questions

### How do Dust and QA.tech compare in monthly traffic?

Dust has 547,217 monthly visits, while QA.tech has 30,550. 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%; QA.tech has -4.4%.

### 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. QA.tech: Paid, Contact for Pricing. Enterprise-style, contact-for-pricing model: the site offers a free getting-started path and a demo booking rather than public per-seat numbers, so exact costs depend on team size, coverage scope and mobile testing needs.

## 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 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 6 | [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) |
| 7 | [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) |
| 8 | [Qase](https://openaitools.app/tool/qase) | 319,213 | -25.5% | Freemium, Free Trial, Contact for Pricing, Free | Ship with confidence: one system of record for manual, automated, and CI tests | [.md](https://openaitools.app/tool/qase.md) |
| 9 | [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) |
| 10 | [Katalon](https://openaitools.app/tool/katalon-studio) | 158,090 | -29.6% | Freemium, Free Trial, Paid, Contact for Pricing | AI-augmented quality platform for web, mobile, API and desktop testing | [.md](https://openaitools.app/tool/katalon-studio.md) |

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Source: https://openaitools.app/compare/dust-vs-qa-tech

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