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Dust 🧩 – Workflow‑Based Agentic AI Platform for Business Operations

Featured image of the Dust logo representing its listing in the AI Solutions Directory at newbits.ai – workflow‑based agentic AI platform designed to integrate language models into real‑world business operations.

Dust is a workflow‑based agentic AI platform crafted to bring language models into real‑world business operations. It enables teams to create autonomous agents that interact with tools like Notion, Slack, and internal APIs — turning multi‑step processes into reliable, AI‑driven workflows.


Built for enterprise readiness, Dust supports reasoning chains, memory, and tool use across multi‑step tasks. Its no‑code visual builder connects company knowledge and apps, while built‑in observability and logging provide the visibility required to run assistants and copilots in sensitive environments at production scale.


🧠 How Dust Drives Agentic AI Workflows


Dust lets you design autonomous agents through a clean visual interface — no code required. Chain reasoning, maintain context with memory, call tools, and integrate directly with business systems (e.g., Notion, Slack, internal APIs) to orchestrate multi‑step automations with oversight.


With observability and logging at the core, teams can monitor behavior, track actions, and ensure governance — making Dust well‑suited for secure, enterprise deployments of internal assistants and LLM‑powered copilots.


🔍 Key Features at a Glance


🖱️ No‑Code Visual Builder – Create agents and workflows via an intuitive canvas

🧠 Reasoning Chains & Memory – Execute multi‑step tasks with context retention

🔌 Tool Integrations – Connect to Notion, Slack, and internal APIs for real work

📊 Observability & Logging – Monitor agent behavior with audit‑friendly detail

🔒 Enterprise‑Grade Deployment – Security‑minded design for production use


🚀 Real‑World Use Cases for Dust


Internal copilots that retrieve and synthesize knowledge from Notion or internal DBs


Cross‑tool automations that notify teams in Slack based on events or data changes


Multi‑step SOP execution with reasoning, memory, and logged actions for review


Secure assistants where visibility, governance, and reliability are mandatory


📌 Example Scenario


A compliance team builds an internal assistant with Dust to manage policy updates. It pulls approved guidance from Notion, applies reasoning checks to proposed edits, posts summaries to stakeholders in Slack, and logs each step for audit — minimizing manual effort while maintaining traceability.



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