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Dust

Enterprise AI / AI Agents · Paris, France / San Francisco, California, USA

Matrix Employer Score™

93.8

High confidence

Employer Intelligence Evidence

Evidence-backed signals supporting our assessment of this AI employer.

Evidence-backed
AI Impact
Medium Confidence
89
3 evidence items
View evidence

Supporting signal

Agent Deployment & Workflow Impact

Agent Deployment & Workflow Impact

Medium Confidence

Oct 9, 2026

Paddle's case reports 342 monthly active users, 114 builders and 470 custom agents after six months of its Dust rollout, with its data and AI leadership identified.

Source: Dust — Paddle customer caseprimaryOpen source ↗

Agent Deployment & Workflow Impact

Medium Confidence

Oct 9, 2026

Bpifrance and Artefact describe deploying Dust to 500 pioneer employees with license governance, risk classification, connector controls and infrastructure monitoring.

Source: Dust — Bpifrance and Artefact caseprimaryOpen source ↗

Enterprise Agent Use

Medium Confidence

Sep 26, 2026

Dust is deployed by organizations as an internal AI assistant and agent platform connected to company knowledge and tools.

Source: DustCompanyOpen source ↗
Evidence items: 3Methodology: v1.2Updated: Oct 9, 2026
AI Leadership
High Confidence
92
3 evidence items
View evidence

Supporting signal

Agentic AI Platform & Autonomy Leadership

Agentic AI Platform & Autonomy Leadership

High Confidence

Oct 7, 2026

Dust documents an Agent Memory tool that retains and updates information across conversations, with memory scoped separately to each user and agent and user controls to inspect and delete saved items.

Source: DustCompanyOpen source ↗

Enterprise Agent Platform

High Confidence

Sep 26, 2026

Dust develops enterprise agents, retrieval, knowledge integration and tool-connected workflows.

Source: DustCompanyOpen source ↗

Agentic AI Platform & Autonomy Leadership

High Confidence

Sep 26, 2026

Dust develops enterprise agents, retrieval, knowledge integration and tool-connected workflows.

Source: DustCompanyOpen source ↗
Evidence items: 3Methodology: v1.2Updated: Oct 7, 2026
Employer Strength
Medium Confidence
91
3 evidence items
View evidence

Supporting signal

AI Agent Employer Strength

AI Agent Employer Strength

High Confidence

Oct 7, 2026

Dust announced a US$40 million Series B in May 2026 with Abstract, Sequoia, Snowflake Ventures and Datadog. This disclosed financing supplies capitalization evidence independent of historical enterprise implementation and security capability.

Source: DustCompanyOpen source ↗

AI Agent Employer Strength

Medium Confidence

Oct 7, 2026

Dust's May 2026 announcement reports use by over 3,000 organizations and identifies Persona deployment across 11 departments and Doctolib's company-wide strategy reaching 3,000 employees. This named organizational adoption footprint is independent of financing and historical generic SaaS implementation capability.

Source: DustCompanyOpen source ↗

Enterprise Saas Execution

Medium Confidence

Sep 26, 2026

Dust demonstrates enterprise SaaS implementation, security and integration capability for internal AI systems.

Source: DustCompanyOpen source ↗
Evidence items: 3Methodology: v1.2Updated: Oct 7, 2026
Market Transferability
High Confidence
96
3 evidence items
View evidence

Supporting signal

Agentic AI Skill Transferability

Agentic AI Skill Transferability

Medium Confidence

Oct 7, 2026

Dust documents preview client-side MCP tooling with dynamic conversation-scoped registration, OAuth authentication, TypeScript/JavaScript SDK transport and SSE plus HTTP communication. This standards-based implementation supports inferred transferable agent integration skills; custom development is required.

Source: DustCompanyOpen source ↗

Enterprise Agent Portability

High Confidence

Sep 26, 2026

Agent, retrieval and enterprise integration skills transfer across knowledge-management and applied AI platforms.

Source: DustCompanyOpen source ↗

Agentic AI Skill Transferability

High Confidence

Sep 26, 2026

Agent, retrieval and enterprise integration skills transfer across knowledge-management and applied AI platforms.

Source: DustCompanyOpen source ↗
Evidence items: 3Methodology: v1.2Updated: Oct 7, 2026

Matrix Employer Score™ components are supported by structured employer evidence, versioned methodologies, and confidence ratings.

Hiring Signal

Hiring

Employer Signal

91

Hiring Opportunity

95

Company Overview

Employer Snapshot

AI Category

Enterprise AI / AI Agents

Primary Location

Paris, France / San Francisco, California, USA

Founded

2023

Employees

120

Why AI Talent Watches Dust

Dust builds collaborative AI agents and enterprise infrastructure designed for teams to deploy and operate AI workflows.

Why Join

Build enterprise AI agents used by teams to automate operational and knowledge workflows.

Employer Intelligence

Hiring: Hiring

Talent Competition: Very High

Technical Bar: Exceptional

AI Talent Matrix Confidence: High confidence

Talent Intelligence

Matrix Employer Score™ Breakdown

View Matrix Employer Score™ Methodology →

Core Employer Intelligence

AI Impact

89

AI Leadership

92

Employer Strength

91

Market Transferability

96

Career & Workplace

Career Growth

100

Compensation

100

Engineering Culture

100

Work-Life Balance

80

Evidence-Backed Signals

Career Upside

100

Talent Density

100

Hiring Opportunity

95

Talent & Career Programs

Remote Policy

Hybrid

Visa Sponsorship

Case by Case

Internship Program

Available

New Grad Program

Available

AI Focus

Enterprise Agents / Human-Agent Collaboration / AI Operations

Flagship Products

Dust AI Agent Platform

Data & Methodology

How AI Talent Matrix interprets this employer

Last Updated

9/5/2026

AI Talent Matrix Confidence

High confidence

AI Talent Matrix scores and signals are comparative employer-intelligence indicators and should not be interpreted as guarantees of hiring, compensation, career outcomes, or individual fit.

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