Assembled builds a company-wide AI operating system with Dust, achieving 95% internal adoption across 120+ employees
Assembled's hypergrowth exposed severe knowledge fragmentation: company information was scattered across Google Drive, Slack, Notion, Linear, Cursor, Snowflake, and more, search was broken, rapid product releases made knowledge quickly obsolete, and individual AI tool usage was siloed with no shared workflows.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · CEO pilots Dust in Slack
Assembled's CEO began experimenting with Dust inside a Slack channel to test small internal workflows.
Tools used
DustZendeskLinearSnowflakeRelayZapier
Outcome
Dust achieved 95% internal adoption across 120+ employees without extensive training, saved hundreds of hours through unified search and AI agents, reduced cross-team interruptions so employees self-serve information, and accelerated new-hire onboarding.
What failed first
Individual automation setups using Relay, Zapier, or personal Claude MCP configurations did not scale because each workflow was tied to a single employee's account and required technical setup most staff could not do.