Customer support · Production

Tilt operationalizes AI customer service across every channel with Ada, achieving 84% automated resolution rate on chat

The problem

As Tilt's customer base grew, their support backlog expanded and high staff turnover made hiring and training a persistent challenge; handling roughly 30,000 emails per month, they needed to scale without adding headcount.

Workflow diagram · grounded in source

Customer initiates authenticated chat

trigger

“In chat, customers must be logged in, giving the AI agent access to richer, account-level context through various APIs.”

Greeting API pulls user context

integration

“Diaz's team developed a greeting API that pulls high-level user information at the start of the conversation.”

AI dynamically filters playbooks

ai_action

“Based on that data, the AI agent can dynamically filter which playbooks, processes, and knowledge to surface, making support more targeted and preemptive from the very first message.”

AI interprets intent and resolves

ai_action

“If someone asks about their credit card but really means debit, the AI can interpret the intent and respond correctly, something a scripted bot couldn't do.”

Conversation insights fed to product team

feedback_loop

“Diaz partners with the product team to share conversational data, including analyzing transcripts to see if AI agent conversations are matching the trends they're seeing elsewhere.”

Reported outcome

Ada's AI agent achieved an 84% automated resolution rate on chat, raised CSAT by 8 points (up to 15 in some cases), reduced email first response time by 9 hours, and reached 94% containment, while generating richer conversational data that the product team uses for strategic decisions.

Reported metrics

Email inquiries resolved without human intervention64%

CSAT increase in some casesas much as 15

Containment rate94%

chat volume handled by AI agent100%

Reported stack

AdaCoaching and Playbooks

Source

https://www.ada.cx/case-study/tilt

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Ada's AI agent achieved an 84% automated resolution rate on chat, raised CSAT by 8 points (up to 15 in some cases), reduced email first response time by 9 hours, and reached 94% containment, while generating richer co…

What tools did this team use?

Ada, Coaching and Playbooks.

What results were reported?

Email inquiries resolved without human intervention: 64%; CSAT increase in some cases: as much as 15; Containment rate: 94%; chat volume handled by AI agent: 100% (source-reported, not independently verified).

How is this customer support AI workflow structured?

Customer initiates authenticated chat → Greeting API pulls user context → AI dynamically filters playbooks → AI interprets intent and resolves → Conversation insights fed to product team.