# How did Kalshi automate customer support with an AI agent?

> Kalshi, whose support volume grew from 30,000 tickets in 2024 toward a projected two million by end of 2026, uses Fin. Intercom reports Fin resolves around 80% of conversations end to end.

- **Evidence grade:** B — Named organization with a quantified outcome, from the vendor or the organization's own announcement.
- **Organization:** Kalshi (prediction market exchange)
- **Industry:** Banking & Financial Services — Prediction markets
- **Roles:** Customer Support
- **Tools:** Fin AI Agent (Intercom)
- **Status:** production · **Agent pattern:** autonomous-agent · **Autonomy:** 3/4
- **Last verified:** 2026-10-17

## Reported outcomes
- automation rate: around 80% resolved end to end [1] (self-reported)

## How it works
1. Fin answers inbound support conversations using the company's help content.
2. Hands unresolved conversations to human agents.

## Risks & compliance
- Incorrect answers to customers; human review and escalation paths needed
- Vendor-published results; not independently audited
- Financial-services disclosures and account security

## Sources
1. Intercom (Fin), "How Kalshi automated 80% of customer support with Fin" (undated; accessed 2026-10-17) <https://fin.ai/customers/kalshi>
   > "Fin is now involved in nearly every support conversation and resolves around 80% of them end to end, without a human stepping in."

Canonical: https://agentcasefile.com/cases/kalshi-fin-ai-agent/ · License: CC BY 4.0 (summary) · Source: Agent Casefile