# Cencurity vs Dust

Cencurity records 0 monthly visits with 0% month-over-month growth and Free pricing. Dust records 547,217 monthly visits with +1.8% growth and Contact for Pricing pricing.

| Metric | [Cencurity](https://openaitools.app/tool/cencurity) | [Dust](https://openaitools.app/tool/dust) |
| :--- | :--- | :--- |
| Website URL | https://cencurity.com | https://dust.tt |
| Categories | AI Developer Tools, AI Agent, Large Language Models (LLMs), Log Management | AI Assistant, Large Language Models (LLMs), AI Workflow, AI Knowledge Management |
| Pricing Model | Free | 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 | 4.2 | 4.4 |
| Saved Count | 0 | 5 |
| Supported Platforms | Website | Website |

## Cencurity

Cencurity is built for teams that have started shipping AI agents and AI-assisted coding workflows and now need a control point over what those agents send and receive. The product places itself between your agents, IDEs and the LLM providers they depend on, so a single integration gives consistent behavior across models, tools and environments without rewriting existing workflows. A centralized dashboard shows every agent call in real time, including requests, responses, latency, policy hits, redactions and blocks.

The core protection model is policy-first. Cencurity detects policy violations as traffic flows, prioritizes the events that matter, and applies zero-click guardrails so security does not become a manual review queue. Sensitive data is identified at the edge and stopped before it reaches a model or a user, and the same pipeline can proxy LLM traffic while automatically redacting sensitive content. Because policies can be run in dry-run mode first, teams can measure the impact of a rule before they enforce it and roll it out gradually.

Operationally, Cencurity is aimed at developers rather than security analysts alone: getting started means opening the repository and following a quickstart, and webhook notifications push verified alerts into tools like Slack and Jira rather than flooding inboxes. Combined with end-to-end log analysis that lets you search, filter and correlate requests, responses and policy decisions, this makes it a practical way to add governance and an audit trail to AI coding without slowing delivery.

**Pricing & Plans:** Cencurity offers a free entry point: the Get Started Free path opens the public repository and quickstart documentation. The site lists no published paid tiers, so larger or managed deployments likely require contacting the team.

- **Real-time leak protection:** Automatically detects and blocks secrets, PII and risky model output before it reaches users or upstream providers.
- **LLM proxy with redaction:** Routes LLM traffic through the gateway and redacts sensitive data inline, so agents keep working while secrets stay out of prompts.
- **Centralized security dashboard:** One pane of glass for requests, responses, latency, policy hits, redactions and blocks across every agent call.
- **End-to-end log analysis:** Search, filter and correlate requests, responses and policy decisions to pinpoint risk in seconds.
- **Dry-run rollout and webhooks:** Measure a policy's impact before enforcement, then push only verified alerts to Slack, Jira and similar tools.

**Strengths:** Covers secrets, PII and risky output in one gateway rather than separate point tools; Works with existing agents and IDEs through one integration, no rewrites required; Dry-run mode lets teams validate policies before enforcing them; Free repository-based quickstart makes evaluation easy for developers

**Limitations:** Pricing beyond the free entry point is not published on the site; Requires developer involvement to deploy and configure policies

[Profile (Markdown)](https://openaitools.app/tool/cencurity.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 Cencurity and Dust compare in monthly traffic?

Cencurity has 0 monthly visits, while Dust has 547,217. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Cencurity has a month-over-month growth rate of 0%; Dust has +1.8%.

### How does pricing compare?

Cencurity: Free. Cencurity offers a free entry point: the Get Started Free path opens the public repository and quickstart documentation. The site lists no published paid tiers, so larger or managed deployments likely require contacting the team. 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 | [Datadog](https://openaitools.app/tool/datadog) | 5,175,760 | -4.8% | Freemium, Free Trial, Paid, Contact for Pricing, Free | Unified observability, security and incident response for cloud-scale engineering teams | [.md](https://openaitools.app/tool/datadog.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 | [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 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.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 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.md) |

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

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