# Dust vs Kiro

Dust records 547,217 monthly visits with +1.8% month-over-month growth and Contact for Pricing pricing. Kiro records 3,330,476 monthly visits with +4.6% growth and Freemium pricing.

| Metric | [Dust](https://openaitools.app/tool/dust) | [Kiro](https://openaitools.app/tool/kiro) |
| :--- | :--- | :--- |
| Website URL | https://dust.tt | https://kiro.dev |
| Categories | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management | AI Code Assistant, AI Code Generator, AI Agent, AI Developer Tools |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 547,217 | 3,330,476 |
| MoM Growth Rate | +1.8% | +4.6% |
| Primary Market | France | United States |
| Direct Visits | 456,919 | 1,814,132 |
| Review Score | 4.4 | 4.5 |
| 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)

## Kiro

Kiro is a spec-driven coding platform from AWS that reframes AI assistance around intent rather than autocompletion. You describe what the software should do and supply context, and Kiro turns that into specifications that guide an agent through planning, implementation, testing, and review. Because requirements and design decisions are written down first, agents can check their results against what you actually asked for, and the platform deliberately enforces quality at each step so agents cannot silently skip a failing test.

The product spans multiple surfaces. Kiro IDE is the familiar desktop experience, the CLI installs with a single command and can run headless in CI/CD, and cloud sessions move long-running tasks off your laptop with parallel agents that keep working after you close the lid. Kiro Crew adds persistent agents that watch your backlog, codebase, or CI pipeline, triage incoming work, spawn specialized bots, and bring results back for your approval. It also meets you where work happens, whether that is Slack, Microsoft Teams, GitHub or GitLab issues and pull requests, or scheduled automation.

Underpinning this is persistent memory across sessions, shared team knowledge, and reusable steering so corrections do not need repeating. Workflows break large tasks into checked steps, property-based tests validate behavior across hundreds of cases, and adversarial review agents scrutinize diffs before a human approves. Kiro supports Claude, GPT, and open-weight models such as DeepSeek and Qwen, with an Auto mode that routes each task to a suitable model, and it is built on open standards including ACP, AGENTS.md, Skills, MCP, and Open VSX extensions.

**Pricing & Plans:** Kiro follows a freemium model with free usage to get started and paid tiers that add higher usage limits and credits for individual developers and teams. Enterprises can contact AWS for governance, SSO, compliance, and predictable pricing arrangements.

- **Specs that verify intent:** You describe intent and context first; Kiro captures requirements and design as specifications, then verifies the finished implementation against them.
- **Persistent agents and Crew:** Kiro Crew watches your backlog, codebase, or CI, triages new work, delegates to specialized bots, and returns results for your review.
- **Workflows and adversarial review:** Long tasks split into checked steps so agents cannot shortcut a failed test, and review agents inspect diffs before a human approves a merge.
- **Runs where you work:** Use the IDE, mobile, or web, run headless in CI/CD with the CLI, or trigger Kiro from Slack, Microsoft Teams, GitHub, and GitLab.
- **Open standards and model choice:** Supports ACP, AGENTS.md, Skills, MCP, and Open VSX extensions, with Claude, GPT, and open-weight models via Auto routing.

**Strengths:** Spec-driven workflow ties generated code back to written requirements and design; Multiple surfaces including IDE, CLI, web, mobile, and cloud sessions; Persistent memory and shared steering reduce repeated corrections across sessions; Built and run by AWS with enterprise governance, SSO, and compliance backing

**Limitations:** Spec-first discipline adds upfront effort compared with prompting a chat assistant; Heavier sessions consume credits, so heavy usage can push you onto paid tiers; Tightest experience is with AWS and its surrounding ecosystem, which may not suit every stack

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

## Frequently Asked Questions

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

Dust has 547,217 monthly visits, while Kiro has 3,330,476. 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%; Kiro has +4.6%.

### 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. Kiro: Freemium. Kiro follows a freemium model with free usage to get started and paid tiers that add higher usage limits and credits for individual developers and teams. Enterprises can contact AWS for governance, SSO, compliance, and predictable pricing arrangements.

## 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 | [Cursor](https://openaitools.app/tool/cursor) | 23,297,751 | +8.4% | Freemium | Provides a polished AI-first code editor experience, but lacks Kiro's native AWS spec-driven planning workflows. | [.md](https://openaitools.app/tool/cursor.md) |
| 4 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Offers powerful parallel AI coding agents across an IDE and CLI, but lacks dedicated AWS ecosystem integrations. | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 5 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Builds and deploys full-stack apps instantly in the cloud, but lacks Kiro's local spec-driven engineering verification. | [.md](https://openaitools.app/tool/replit.md) |
| 6 | [VS Code](https://openaitools.app/tool/vs-code) | 7,397,370 | -3.8% | Freemium | Write code with precision, hand bigger jobs to agents, and keep working from anywhere | [.md](https://openaitools.app/tool/vs-code.md) |
| 7 | [Qoder](https://openaitools.app/tool/qoder) | 5,145,040 | +81.8% | Freemium, Free Trial, Free | Reads entire codebases to execute multi-file tasks as an IDE plugin, but offers less structured spec management. | [.md](https://openaitools.app/tool/qoder.md) |
| 8 | [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) |
| 9 | [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) |
| 10 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Operates fully autonomously across entire repositories to open pull requests, but lacks an integrated interactive IDE workspace. | [.md](https://openaitools.app/tool/devin.md) |

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

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