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Dust

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At a glance

Price
Pricing on request
Vendor
Dust

Specifications & properties

Key decision factors

Pricing model
Freemium 1
Agent type
  • Workflow automation
1
Audit logs / traceability
Yes 1

Pricing

Free tier
Yes 1
Billing model
Per seat 1

Integration

API available
Yes 1

Capabilities

Multi-agent orchestration
Yes 1

Model

Model choice
Multiple models 1
Report data / suggest a correction

Metrics vs. the category

Integrations count
n/a

Platform for teams to create customizable, secure AI agents powered by leading LLMs and connected to company knowledge and tools; EU-founded vendor with per-seat plans.

Profile

Dust is an AI agent platform for internal company workflows, letting teams build agents that draw on internal knowledge and tools to answer questions, automate tasks, and coordinate with each other, aimed at organizations that want a company-wide AI layer rather than a single-purpose chatbot.

Who it's for

Dust is built for operations, engineering, support, and knowledge teams inside companies that already have a lot of internal documentation, tools, and processes and want AI agents that can search across them and take action, rather than developers building a standalone consumer product. It's commonly adopted company-wide rather than by a single department, since its per-seat pricing model assumes broad internal rollout.

How it works

Teams build agents in Dust by connecting them to internal data sources and tools, then giving them specific instructions and permissions for what they're allowed to do. Multi-agent orchestration lets more complex requests be broken down and routed between several specialized agents rather than relying on one general-purpose assistant, and because Dust supports multiple underlying AI models, teams can choose the model that best fits a given agent's task. An API is available for embedding Dust's agents into other internal tools, and audit logs track agent activity for internal governance and review.

Pricing

Dust has a free tier for trying the platform, with paid plans billed per seat rather than by usage credits — though our data doesn't include a specific starting price, so check Dust's current pricing page for exact per-seat rates. Because pricing is per-seat, cost scales predictably with headcount using the platform rather than with how heavily agents are used, which is worth factoring in for larger rollouts.

Strengths and trade-offs

Dust's strength is being built specifically for company-wide internal AI use: multi-agent orchestration, multi-model support, API access, and audit logs together support both flexibility and governance as adoption grows across a company. The trade-off is that, as a per-seat product, cost grows directly with how many employees have access regardless of how much they use it, and it's a cloud-only platform with no self-hosted option documented in our data. For companies wanting to give many employees access to internal AI agents rather than deploying a single specialized bot, Dust is a strong option alongside similar internal-agent platforms like Glean and Cassidy. Teams should also factor in that seat-based pricing rewards broad adoption, so a pilot with a small group may not reflect the eventual per-seat economics of a company-wide rollout.

Frequently asked questions

How much does Dust cost?

Dust has a free tier for trying the platform, with paid plans billed per seat; our data doesn't include a specific starting price, so check Dust's current pricing page for exact per-seat rates.

Can I self-host Dust?

No self-hosted deployment option is documented in our data; Dust is offered as a cloud platform. Teams with on-premises requirements should confirm current deployment options directly with Dust.

Does Dust support multi-agent orchestration and multiple AI models?

Yes. Dust can break a complex request down and route it between several specialized agents rather than relying on a single general-purpose assistant, and it supports multiple underlying AI models so teams can pick the best fit for a given agent's task.

Dust vs. Glean?

Both are internal AI agent platforms built for company-wide knowledge work with multi-agent capabilities and enterprise governance features like audit logs. Glean is often chosen for its strength as an enterprise search layer across many connected systems, while Dust is frequently picked for its flexible, multi-model agent-building experience — worth trialing both against your specific internal data sources.

Does Dust offer an API, and is it GDPR-compliant?

Yes, Dust provides an API for embedding its agents into other internal tools, and it includes audit logs for internal governance. Specific GDPR hosting terms and EU data-residency options aren't detailed in our data, so EU-based teams should confirm current data-processing terms directly with Dust.