# Dust vs SciFig

Dust records 547,217 monthly visits with +1.8% month-over-month growth and Contact for Pricing pricing. SciFig records 91,473 monthly visits with +4.7% growth and Freemium pricing.

| Metric | [Dust](https://openaitools.app/tool/dust) | [SciFig](https://openaitools.app/tool/scifig) |
| :--- | :--- | :--- |
| Website URL | https://dust.tt | https://scifig.ai |
| Categories | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management | AI Image Generator, AI Background Remover, AI Image Enhancer, AI Image Upscaler |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 547,217 | 91,473 |
| MoM Growth Rate | +1.8% | +4.7% |
| Primary Market | France | United States |
| Direct Visits | 456,919 | 23,551 |
| Review Score | 4.4 | 4.1 |
| 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)

## SciFig

SciFig is built around the observation that most papers need more than one kind of figure, and that juggling several unrelated tools for illustrations, plots and diagrams wastes time. Its Illustration workspace accepts six input modes: a written description, a rough sketch, a lab photo, a PDF of an existing paper, a reference figure to imitate in style, and photo-to-figure conversion. From any of these it produces scientific images of mechanisms, pathways, cross-sections and graphical abstracts, drawing on hundreds of templates across multiple disciplines.

The DataChart workspace is the quantitative side. Upload a CSV or Excel file, describe the chart you want, and SciFig plots it in journal-consistent styles with colorblind-safe palettes. The chart library is deliberately deep and organized by research need — basic and trend charts, distribution and statistics plots such as violin, box and raincloud charts, relationship and model plots like regression and Bland–Altman, biomedical staples including volcano plots and Kaplan–Meier survival curves, plus flows and structures such as heatmaps and Sankey diagrams. Charts ship with the statistics and the Python code that produced them, which matters when a reviewer asks how a figure was made.

FlowChart covers the qualitative diagrams: PRISMA and CONSORT screening flows, model architectures, cycle diagrams and research timelines, described in plain language and returned as editable diagrams rather than static images. Across all three engines the editability is the real differentiator — you can retype a label, redraw one region, switch journal style or palette, or move a box and its arrows without regenerating the whole figure. Export options include editable PPTX, layered SVG, 8K PNG/JPG, and for data charts also PDF, EPS and TIFF, so figures survive poster, manuscript and presentation formats alike.

**Pricing & Plans:** Freemium. New users start with up to 150 free credits and can reach about 250 free credits on day one when joining through an invite, with no credit card required. Paid plans and credit packs are available, and the site states paid credits never expire. Pricing changes with promotions, so check the pricing page for current plan details.

- **Three dedicated engines: Illustration, DataChart and FlowCha:** Three dedicated engines: Illustration, DataChart and FlowChart for scientific images, data plots and protocol diagrams respectively
- **Six illustration input modes: text, sketch, photo, PDF, refe:** Six illustration input modes: text, sketch, photo, PDF, reference figure and photo enhancement, backed by hundreds of discipline-specific templates
- **Data charts straight from CSV or Excel across around 50 char:** Data charts straight from CSV or Excel across around 50 chart types, including volcano plots, survival curves, forest plots and heatmaps
- **Fully editable output: change any label, recolor, redraw a r:** Fully editable output: change any label, recolor, redraw a region or shift a box and its arrows without regenerating the figure
- **Researcher-friendly export: layered SVG, editable PPTX, 8K P:** Researcher-friendly export: layered SVG, editable PPTX, 8K PNG/JPG, plus PDF, EPS and TIFF for charts, with journal styles and colorblind-safe palettes

**Strengths:** Purpose-built for research figures rather than generic AI image generation, with journal styles and colorblind-safe palettes; Strong editability after generation, so a figure can be refined instead of regenerated from scratch; Data charts are plotted from your actual numbers and come with the statistics and Python code; Wide export coverage including layered SVG, editable PPTX and print-grade TIFF/EPS

**Limitations:** Scientific accuracy still depends on your input: descriptions and extracted text must be checked before publication; Credit-based pricing means heavy figure production can consume the allowance quickly; The enormous tool and template catalog can feel overwhelming for a first-time user

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

## Frequently Asked Questions

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

Dust has 547,217 monthly visits, while SciFig has 91,473. 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%; SciFig has +4.7%.

### 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. SciFig: Freemium. Freemium. New users start with up to 150 free credits and can reach about 250 free credits on day one when joining through an invite, with no credit card required. Paid plans and credit packs are available, and the site states paid credits never expire. Pricing changes with promotions, so check the pricing page for current plan details.

## 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 | [ConceptViz](https://openaitools.app/tool/conceptviz) | 157,061 | +28.1% | Freemium, Paid | Editable scientific figures and graphical abstracts from a prompt | [.md](https://openaitools.app/tool/conceptviz.md) |
| 9 | [SciDraw AI](https://openaitools.app/tool/scidraw-ai) | 146,452 | +10.1% | Freemium | AI scientific figure and data chart generator for researchers | [.md](https://openaitools.app/tool/scidraw-ai.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-scifig

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