# Dust vs Solarch

Dust records 547,217 monthly visits with +1.8% month-over-month growth and Contact for Pricing pricing. Solarch records 742 monthly visits with +286.5% growth and Freemium pricing.

| Metric | [Dust](https://openaitools.app/tool/dust) | [Solarch](https://openaitools.app/tool/solarch) |
| :--- | :--- | :--- |
| Website URL | https://dust.tt | https://solarch.dev |
| Categories | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management | AI Code Generator, AI Diagram Generator, AI Developer Tools, AI Code Assistant |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 547,217 | 742 |
| MoM Growth Rate | +1.8% | +286.5% |
| Primary Market | France | United States |
| Direct Visits | 456,919 | 219 |
| Review Score | 4.4 | 4.3 |
| 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)

## Solarch

Solarch inverts the usual AI coding flow. Rather than generating code and hoping the architecture catches up, it produces architecture first: you draw your backend as a node/edge graph using 21 node types across 8 families and 16 typed relationships, and a default-deny Rules Engine validates every connection as you draw it. Concepts like a controller reaching directly into a database table are simply not drawable, so structural mistakes are caught at design time instead of in code review.

Once a graph is validated, a hybrid code engine takes over. Stage one is a deterministic compiler that turns nodes and edges into a skeleton — DTOs, entities, constructor injection — using no model tokens at all. Stage two applies AI surgically to fill only the empty function bodies, so the algorithmic logic stays yours and roughly 80% of a project ships as boilerplate. Graphs are organised fractally: each node lives in one home tab and other tabs import it as a ghost reference rather than making a copy, which keeps large systems coherent, and semantic zoom lets you move from macro modules down to micro-graphs.

The architecture then travels with you. A VS Code extension shows a revision timeline and live drift findings in the Problems panel; the CLI provides drift guard, two-way sync and deterministic NestJS code generation and can block merges that break the architecture in CI; and an MCP server supplies Claude, Cursor and other agents with the real graph plus the rules, so every write only commits when the edges pass. Type safety runs from the database schema through the API contract to the typed client, and changing a column stops the frontend compiling until it is reconciled.

**Pricing & Plans:** A free-forever tier covers two projects, the live canvas, the AI architect and default-deny validation with no credit card. Paid tiers run Draw at $5/month for unlimited sketchpad use, Build at $20/month for extended AI usage plus code generation and ZIP export, Code at $100/month for full codebase generation, and Team at $30 per seat for shared projects. A 7-day trial applies to paid plans, and Enterprise adds self-hosting, SSO, audit logs, a custom rules matrix and dedicated support.

- **Live node/edge canvas:** Model the whole backend — controllers, services, repositories, tables, DTOs and queues — on one surface with 16 semantic edge types across 8 families.
- **Default-deny rules engine:** An illegal connection such as wiring a controller straight to a table is rejected the instant you draw it, based on 7 anti-patterns and 3 conditional checks.
- **Hybrid code engine:** Stage one compiles the graph deterministically into skeletons with zero tokens; stage two uses surgical AI to fill only the empty function bodies.
- **GraphRAG grounding:** A LangGraph-powered architect grounds every plan in a vector-indexed library of canonical patterns instead of autocompleting from scratch.
- **Developer tooling:** VS Code extension, CLI with drift guard and two-way sync, and an MCP server so AI agents work against the real, rule-checked architecture.

**Strengths:** Architecture is validated before any code is written, so drift is structurally prevented; Deterministic stage-one generation keeps token costs low; Writes commit only when the graph passes the rules, not just when the model feels confident; Same diff engine across editor, CLI and AI agent

**Limitations:** Requires willingness to model the system as a graph before coding; Deterministic generation is currently deepest for NestJS-style backends; The full codebase tier is a serious monthly commitment for individuals

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

## Frequently Asked Questions

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

Dust has 547,217 monthly visits, while Solarch has 742. 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%; Solarch has +286.5%.

### 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. Solarch: Freemium. A free-forever tier covers two projects, the live canvas, the AI architect and default-deny validation with no credit card. Paid tiers run Draw at $5/month for unlimited sketchpad use, Build at $20/month for extended AI usage plus code generation and ZIP export, Code at $100/month for full codebase generation, and Team at $30 per seat for shared projects. A 7-day trial applies to paid plans, and Enterprise adds self-hosting, SSO, audit logs, a custom rules matrix and dedicated support.

## 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 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | A spec-driven AI IDE and agent platform that plans, builds, reviews, and verifies real engineering work. | [.md](https://openaitools.app/tool/kiro.md) |
| 4 | [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) |
| 5 | [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) |
| 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 | [Eraser](https://openaitools.app/tool/eraser) | 534,396 | -23.6% | Freemium, Paid, Contact for Pricing | AI diagrams and technical design docs built from your code and systems | [.md](https://openaitools.app/tool/eraser.md) |
| 8 | [Convex](https://openaitools.app/tool/convex) | 390,417 | -18.7% | Freemium, Paid | Reactive TypeScript backend with database, functions and AI gateway | [.md](https://openaitools.app/tool/convex.md) |
| 9 | [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) |
| 10 | [Augment Code](https://openaitools.app/tool/augment-code) | 326,215 | +24.1% | Freemium, Free Trial, Contact for Pricing | Agent orchestration platform for your whole software development lifecycle | [.md](https://openaitools.app/tool/augment-code.md) |

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

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