DUST AGENCY: BUILD AI ASSISTANTS THAT ACTUALLY WORK

STEP 1: AI USE CASE AUDIT

We start by understanding what you want to automate and where AI can actually help. We audit your current processes, identify repetitive tasks that AI can handle, and map your data sources (documents, databases, APIs). We also check what you’ve already tried with AI and what worked or didn’t. We list concrete use cases ranked by impact and feasibility. We identify which data sources to connect and what integrations you need. We define 2-3 priority assistants to build first, with clear success metrics. At the end of this step, you have a roadmap of AI assistants to build and a clear plan for your Dust workspace.

STEP 2: WORKSPACE AND DATA SETUP

We configure your Dust workspace and connect all your data sources. We set up your workspace structure, configure team permissions, and connect your knowledge bases (Notion, Google Drive, Confluence, Slack channels). We also configure API connections to your internal tools and databases. We test retrieval quality with different chunking strategies and embedding configurations. We make sure your assistants will access the right information with proper context. We set up data sync schedules and access controls. We configure managed data sources for sensitive information. At the end of this step, your Dust workspace is ready with all data sources connected and properly indexed for semantic search.

STEP 3: ASSISTANT DEVELOPMENT

We create your custom AI assistants with specialized instructions and tools. We write detailed system prompts with clear instructions, examples, and guardrails. We configure which data sources each assistant can access and what tools it can use (API calls, web search, code execution). We develop custom tools and API integrations for specific actions (updating your CRM, creating tickets, sending notifications). We test assistant responses with real queries and edge cases. We iterate on prompts and tool configurations based on actual outputs. We add few-shot examples and refine instructions until responses are consistently good. At the end of this step, you have functional assistants that understand their role and can access your data and tools.

STEP 4: WORKFLOW INTEGRATION

We integrate your assistants into your daily workflows and tools. We connect Dust to Slack so your team can interact with assistants directly in channels. We set up API workflows that trigger assistants automatically (new ticket → assistant analyzes and routes it). We create custom integrations with your tools (HubSpot, Airtable, your internal systems) using Dust’s API and webhook capabilities. We configure conversation histories and context management. We test end-to-end workflows with real scenarios. We make sure assistants handle errors gracefully and escalate to humans when needed. At the end of this step, your assistants are embedded in your workflows and your team can use them naturally throughout their day.

STEP 5: TRAINING AND OPTIMIZATION

We train your team and optimize assistants based on real usage. We run training sessions showing how to use each assistant, when to use which one, and how to get the best results. We share best practices for prompting and interacting with AI agents. We monitor usage analytics, track common queries, and identify patterns. We analyze where assistants perform well and where they struggle. We iterate on prompts, add new examples, refine data source configurations, and improve tool integrations based on feedback. We add new assistants for emerging use cases. At the end of this step, your team is autonomous with Dust and your assistants keep improving based on real-world usage data.

WHY WORK WITH US?

AN AGENCY THAT USES DUST FOR CLIENTS EVERY DAY

At Hack’celeration, we don’t just do Dust agency work. We master the whole automation stack (Make, n8n, Airtable, Notion, HubSpot) and know how to integrate Dust into any system. We also work with other AI platforms (OpenAI, Anthropic, custom models) and understand when Dust is the right choice versus building something custom.

We work with tech startups building AI features into their products, scale-ups automating support and ops, and agencies delivering AI capabilities to their clients. We’ve worked across SaaS, e-commerce, consulting, and internal tools.

We’ve built customer support assistants that handle tier-1 tickets and escalate complex cases, research agents that analyze documents and synthesize insights, sales assistants that qualify leads and update CRMs automatically, and internal knowledge assistants that answer team questions with context from all company docs. We’ve configured semantic search over 100k+ documents with optimized chunking and retrieval, integrated Dust with complex APIs and webhooks, and built multi-agent systems where specialized assistants collaborate on tasks.

We understand both the AI/ML side (prompt engineering, retrieval strategies, model selection) and the business side (what actually saves time versus AI theater). We know the limitations of LLMs and design assistants that work within those constraints.

We don’t skim features. We give you a production-ready AI system with proper error handling, monitoring, and governance. We share templates, documented workflows, and lessons from dozens of real deployments.

You work with a team that has deployed Dust for companies handling thousands of AI conversations per month and knows exactly how to architect assistants that scale and stay reliable.