How Electra's customer care team handles complex support tickets 80% faster with Dust
Electra's customer care team faced a scaling challenge as ticket volume grew with European expansion, with complex escalated tickets requiring agents to pull information from multiple disconnected systems. The company also needed an AI solution accessible to non-technical staff while satisfying cybersecurity's data governance requirements, which scattered generic ChatGPT licenses could not meet.
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 · Escalated ticket arrives
A human agent receives an escalated ticket from Intercom.
Tools used
DustIntercomMCP
Outcome
The three Dust customer care agents reduced time per escalated ticket by 80%, with complex tickets now handled in about 3 minutes. The agents average 4 new AI conversations per hour. Company-wide, Dust reached 70% weekly active users within the first month of its September 2025 launch, stabilizing at 70–80%.
What failed first
Electra had previously distributed generic ChatGPT licenses across teams, but cybersecurity had no visibility into what company data was being shared with AI tools and could not enforce compliance policies or measure data access.