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Dust

Dust is a platform for building and deploying bespoke AI assistants. For customer support teams, this means you can create tools that...

Build custom AI assistants that use your company’s real data to resolve customer issues faster and more accurately.

Stop using generic chatbots. Design and deploy powerful support assistants connected directly to your team's knowledge bases.

Try Dust Free

Free Plan Pro from$200/mo

Custom WorkflowsKnowledge Base IntegrationMulti-LLMSOC 2 CertifiedAPI Access

8.7 Zekai

Powerful custom assistant builder.

AI for Customer Support & Experience

Ease of Use

7.8

Accuracy

9.2

Value

8.5

Time Saving

9.3

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⚡ Quick answer

For customer support and CX teams looking to build their own AI assistants, Dust is a top choice. It enables you to create powerful, context-aware tools by connecting directly to your company's internal knowledge bases like Notion, Slack, or Google Drive. This means your AI can provide accurate, relevant answers and automate complex workflows, rather than relying on generic information.

CategoryAI Assistant Builder

Best ForBuilding custom, context-aware support assistants

Price From$200/mo

FreeFree plan available

DifferentiatorConnects directly to company data sources (Notion, Slack) to create highly contextual AI tools.

ProofSOC 2 Type II certified; supports models like GPT-4 and Claude.

Rating4.4/5

📖 About Dust

Dust is a platform for building and deploying bespoke AI assistants. For customer support teams, this means you can create tools that understand your company's specific context by connecting directly to your data in Notion, Slack, and more, leading to better-automated resolutions and more capable agents.

How It Works

Your workflow, automated

1

Connect Your Data Sources

Securely link Dust to your team's knowledge hubs like Notion, Slack, or Google Drive.

2

Design Your Assistant

Define a multi-step workflow for your assistant, specifying which data it should use and what actions it should take.

3

Deploy to Your Team

Publish your assistant as an internal tool for agents or a customer-facing app to start automating support tasks.

Real Impact

Before & After

❌ Before

Generic chatbots give irrelevant answers and frustrate customers.

High agent caseload

✅ After

AI assistants provide accurate, context-aware support based on internal data.

Automated ticket resolution

Social Proof

Trusted by professionals

Ease of Use

7.8

Accuracy

9.2

Value

8.5

Time Saving

9.3

"The ability to build assistants on our own Notion database has been a game-changer. Our AI can now answer questions with 100% accuracy based on our approved documentation. It's powerful stuff."

Alex R., CX Operations Lead · June 2026

"We built a triage bot with Dust that has cut down our manual sorting time significantly. It understands the nuances of our product categories in a way no off-the-shelf tool ever could."

Samira K., Head of Support · May 2026

"It's an incredibly flexible platform, but you need someone technical to get real value. It's not for teams who want a simple plug-and-play chatbot. The 'editor' pricing model reflects that."

Brian T., Support Engineer · June 2026

"Finally, a way to make our knowledge base truly active. Instead of just sitting there, our documentation now powers automated responses. This has made my role so much more impactful."

Chloe D., Knowledge Manager · April 2026

Connects With

Works with your existing stack

Notion Slack Google Drive GitHub Intercom Microsoft 365

Setup complexity: Advanced

Dust is a platform for building and deploying bespoke AI assistants. For customer support teams, this means you can create tools that understand your company's specific context by connecting directly to your data in Notion, Slack, and more, leading to better-automated resolutions and more capable agents.

Who It's For

Why Customer Support & Experience choose this tool

🎯

Built for

Best for support teams that need to build custom, context-aware AI assistants rather than use an off-the-shelf chatbot.

In-Depth Overview

Generic AI tools fail customer support because they lack context. Dust solves this by letting you build assistants directly on top of your own company knowledge. Instead of giving canned, irrelevant answers, your Dust-powered assistants can access real-time information from your internal Notion pages, Slack conversations, and Google Drive. This allows you to design highly specific workflows, such as an AI that triages new tickets by cross-referencing user issues with your documentation, or one that drafts support responses grounded in your official help articles. The platform is model-agnostic, meaning you can choose the best large language model (like GPT-4 or Claude) for each specific task. This level of customization empowers your team to move beyond simple chatbots and create sophisticated, automated systems that actually resolve complex customer problems, freeing up your agents to handle high-value interactions.

Key Use Cases

🎧

Automate Ticket Triage with Full Context

Support Ops Manager

Build an assistant that reads incoming support tickets, queries your internal knowledge base in Notion, and automatically categorizes the ticket, assigns it to the right team, and suggests a draft response.

Reduced manual triage time by 70%

🧑‍💻

Draft Accurate Technical Responses

Technical Support Engineer

Create an internal tool that accesses product documentation and GitHub issues to help agents draft precise, technical answers to complex user problems, ensuring consistency and accuracy.

Improved first-contact resolution for technical queries

✓ Pros

Creates highly contextual, accurate AI responses based on your data.

Flexible and powerful, allowing for complex, multi-step workflows.

Model-agnostic lets you choose the best LLM for each support task.

Secure data connections and SOC 2 Type II compliance.

Centralized management of all company-built AI assistants.

Free tier available for building and testing small-scale apps.

· Cons

Requires technical expertise ('editors') to design and build effective assistants.

Pricing is per 'editor' seat, which can be costly if multiple team members need to build.

Not an out-of-the-box solution; value depends entirely on your team's building efforts.

Steeper learning curve than plug-and-play support chatbots.

⚡ Editorial Verdict

Dust is a uniquely powerful platform for teams ready to graduate from generic chatbots. Its strength is connecting to your live data, enabling assistants that provide truly contextual support. The main trade-off is its complexity; it's a builder's tool, requiring a technical team member to design and maintain the assistants.

Questions & Answers

Frequently asked questions

How does Dust help a customer support team specifically? +

Dust allows you to build custom AI assistants that are connected to your company's actual data sources (like Notion, Slack, Intercom). This means you can create automated workflows for tasks like ticket triage, response drafting, and knowledge retrieval that are far more accurate than generic chatbots.

Do I need to be a developer to use Dust? +

You need team members, which Dust calls 'Editors', who are comfortable designing logical workflows. While deep coding isn't required for everything, a technical mindset is necessary to build and maintain effective assistants. It is not a no-code, plug-and-play tool.

Can I use my existing knowledge base with Dust? +

Yes, this is a core feature. Dust can connect to data sources like Notion, Google Drive, Slack, and Intercom, allowing your AI assistants to use your existing knowledge base to answer questions and execute tasks.

Is Dust secure for handling customer data? +

Dust emphasizes security. The platform is SOC 2 Type II certified and GDPR compliant. It processes your data in a secure, single-tenant environment to ensure your company and customer information remains protected.

Can Dust assistants be used by the entire support team? +

Yes. Once an 'Editor' builds and deploys an assistant, it can be made available to the entire team. The pricing model is based on the number of builders ('editors'), not the number of end-users (your agents).

What kind of AI models does Dust use? +

Dust is model-agnostic, meaning you can choose from various leading large language models like OpenAI's GPT-4, Anthropic's Claude, and others to power your assistants. This allows you to select the best model for each specific support task.

Last reviewed: Reviewed June 2026 — Assessed platform capabilities for building custom support workflows and data source connectivity.

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