# SandboxAQ (CryptoSense) vs Dust

SandboxAQ (CryptoSense) records 0 monthly visits with 0% month-over-month growth and Contact for Pricing pricing. Dust records 547,217 monthly visits with +1.8% growth and Contact for Pricing pricing.

| Metric | [SandboxAQ (CryptoSense)](https://openaitools.app/tool/cryptosense-com) | [Dust](https://openaitools.app/tool/dust) |
| :--- | :--- | :--- |
| Website URL | https://cryptosense.com | https://dust.tt |
| Categories | AI Models, AI Healthcare, AI Medical Diagnosis, AI Research Tool | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 0 | 547,217 |
| MoM Growth Rate | 0% | +1.8% |
| Primary Market | Global | France |
| Direct Visits | 0 | 456,919 |
| Review Score | 4.6 | 4.4 |
| Saved Count | 0 | 5 |
| Supported Platforms | Website | Website |

## SandboxAQ (CryptoSense)

SandboxAQ is an enterprise software company that develops Large Quantitative Models (LQMs): AI systems designed to answer scientific and security questions with quantitative, verifiable outputs rather than generated text. Instead of producing prose, LQMs combine physics simulations, chemistry knowledge and proprietary datasets to predict molecular behavior, material properties or cryptographic risk. The company frames this as "quantitative AI" — models that understand the physical world and support decisions in regulated, high-stakes industries.

The product portfolio is organized around verticals. In life sciences, BioSim LQMs and workflows support virtual screening, antibody design, lead optimization and toxicity prediction. In chemicals and materials, ChemSim models drive catalyst design, alloy development and solid-state battery modeling. In security, AQtive Guard delivers cryptographic discovery, inventory and post-quantum migration planning — technology that originated with CryptoSense, whose domain now redirects here. AQNav addresses GPS-denied navigation, and AQMed targets medical diagnostics such as cardiac triage.

SandboxAQ works with large enterprises, governments and research institutions, and has partnered with model providers such as Anthropic to expose LQM capabilities through familiar LLM interfaces. Because deployments are scoped to each organization's data and workflows, pricing is handled through a contact-sales process rather than published self-serve plans.

**Pricing & Plans:** Enterprise, contact-for-pricing model. SandboxAQ does not publish self-serve tiers; prospective customers request a demo and work with the sales team to scope deployments across LQMs, AQtive Guard, AQNav and AQMed.

- **Large Quantitative Models (LQMs):** AI models grounded in physics, chemistry and proprietary scientific data that return quantitative, no-hallucination outputs for real-world problems.
- **BioSim for drug discovery:** Workflows and scientific modules for virtual screening, antibody design, lead optimization, toxicity prediction and biomarker development.
- **ChemSim for materials science:** Catalyst design, alloy development, battery modeling and property prediction using DFT-based methods and generative AI.
- **AQtive Guard cybersecurity:** Cryptographic discovery, inventory and post-quantum migration planning, built on technology originally developed by CryptoSense.
- **AQNav and AQMed:** Quantum-sensing-based navigation for GPS-denied environments and AI-assisted medical diagnostics such as emergency cardiac triage.

**Strengths:** Backing and partnerships from major investors and collaborators, plus a landmark $500M CHIPS R&D award; Physics- and chemistry-grounded models designed to reduce hallucination in scientific workflows; Broad portfolio covering pharma, materials, cybersecurity, navigation and medical diagnostics; Interoperates with mainstream LLMs, letting teams access LQMs through familiar interfaces

**Limitations:** No published pricing or free trial; access requires a sales conversation; Enterprise and government focus means limited self-serve options for individuals or small teams; Several products are specialized and require domain expertise to deploy effectively

[Profile (Markdown)](https://openaitools.app/tool/cryptosense-com.md)

## 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)

## Frequently Asked Questions

### How do SandboxAQ (CryptoSense) and Dust compare in monthly traffic?

SandboxAQ (CryptoSense) has 0 monthly visits, while Dust has 547,217. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

SandboxAQ (CryptoSense) has a month-over-month growth rate of 0%; Dust has +1.8%.

### How does pricing compare?

SandboxAQ (CryptoSense): Contact for Pricing. Enterprise, contact-for-pricing model. SandboxAQ does not publish self-serve tiers; prospective customers request a demo and work with the sales team to scope deployments across LQMs, AQtive Guard, AQNav and AQMed. 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.

## 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 | [Dr.Oracle](https://openaitools.app/tool/dr-oracle) | 723,847 | -1.2% | Free Trial | Guideline-directed medical answers with citations, built for clinicians | [.md](https://openaitools.app/tool/dr-oracle.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 | [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) |
| 9 | [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) |
| 10 | [Sim AI](https://openaitools.app/tool/sim-ai) | 140,953 | +20.6% | Freemium, Paid (per user/month), and Enterprise with custom pricing; self-hosting free under Apache 2.0 | Open-source workspace to build, deploy and govern AI agents | [.md](https://openaitools.app/tool/sim-ai.md) |

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Source: https://openaitools.app/compare/cryptosense-com-vs-dust

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