DoorDash builds a generative AI voice self-service contact center with Amazon Bedrock and Anthropic's Claude
DoorDash handles hundreds of thousands of support calls per day from Consumers, Merchants, and Dashers, but most calls were still being redirected to live agents despite an existing IVR. Dashers' preference for phone support while driving made response latency a critical constraint, and the team needed a scalable self-service solution that could resolve common inquiries quickly without sacrificing quality.
DoorDash completed rollout in early 2024 of a generative AI voice self-service solution—built in only 2 months—that now handles hundreds of thousands of Dasher support calls per day, driving large and material reductions in call volumes and reducing escalations to live agents by thousands per day.
The prior IVR had already achieved a 49 percent reduction in agent transfers and $3M in YoY operational cost savings; the new Bedrock solution reduced AI development time by 50 percent and achieved a response latency of 2.5 seconds or less.
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Frequently asked questions
What did this team achieve with this AI workflow?
DoorDash completed rollout in early 2024 of a generative AI voice self-service solution—built in only 2 months—that now handles hundreds of thousands of Dasher support calls per day, driving large and material reducti…
What tools did this team use?
Amazon Bedrock, Amazon Connect Customer, Anthropic's Claude, Claude 3 Haiku, Amazon Lex, Knowledge Bases for Amazon Bedrock, Amazon SageMaker, RAG.
What results were reported?
agent transfers reduction (existing IVR): 49 percent; first contact resolution increase (existing IVR): 12 percent; YoY operational cost savings (existing IVR): $3M; Time to build and test solution: 2 months (source-reported, not independently verified).
How is this call center ai AI workflow structured?
Dasher calls support → IVR self-service experience → RAG knowledge retrieval → Claude generates response → Low-latency voice response delivered → Complex issues routed to live agents → Automated test and evaluation.