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Redefining Customer Support: Swiggy’s Enterprise-Scale AI Agent Built with Databricks

See how Swiggy and Databricks partnered to automate and personalize millions of customer interactions — delivering instant, empathetic, scalable support in digital commerce. Skip to main content Summary Swiggy’s Transformation With Enterprise AI Agents: How Swiggy and Databricks designed and scaled a ground-breaking AI solution to automate and personalize customer support at a massive scale. We defined key KPI for operations (like p99 latency < 500ms) and quality (accuracy > 99%), and enabled an alert mechanism when operational KPI or quality KPI do not meet the defined standards.

Agent or tool
Databricks
Topic
Customer Support
Reported on
Case study (Databricks)
Added
2026-11-11

Why it matters

Support is repetitive and time-sensitive. Agents can draft answers, look things up and handle simple requests, so people can focus on the tricky ones. It is one of 554 sightings filed under Customer Support on Agent Sightings (number 479 by interest), and one of 37 involving Databricks.

How you could try it

Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into Databricks or any similar agent and adjust the details to your situation.

I want an agent to handle routine customer questions end to end, and pass anything unclear to a person. The tool in the source case was Databricks.

Saved

Tip: Start small: run it once on a low-stakes example, read what the agent did, and only then let it run on real work.

Source

Read the original first-hand account on Case study (Databricks): https://databricks.com/blog/redefining-customer-support-swiggys-enterprise-scal…. Our summary is a paraphrase; details are in the source.

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