customer_support · finance · workflow
How AI Agents Are Transforming Customer Service with Freshworks Freddy AI
Customer service teams face rising ticket volumes, repetitive queries, and rigid legacy chatbots that break when conversations deviate from preset scripts, leaving customers frustrated with incomplete or impersonal responses.
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 · Customer query received
A customer types a question in natural language on any channel, and the AI Agent instantly detects the intent, tone, and context using large language models.
Tools used
Freddy AI AgentFreddy AI Agent StudioFreddy AI CopilotRAGLLMs
Outcome
PhonePe automates 60% of its queries to serve 150 million customers using Freshworks. Freshworks positions Freddy AI Agent as delivering significant cost savings compared to per-resolution pricing competitors.
What failed first
Traditional chatbots relying on rigid scripts and flows fail to handle multi-part or off-script queries, forcing customers to repeat themselves and escalating frustration.
Results
Volume60%
Cost replaced86%
Grounding & classification
Source type: generic use case
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agent assistagentic workflowconversational aiknowledge searchragsupport agentchat transcriptknowledge basesupport ticketfailure mode describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedecommercefinancial servicesautomation ratecost reductiondeflection rategeneric use casecustomer supportticket triageautonomous resolutionescalation workflowrag answering