Case Study
Replacing hours of daily busywork with a single Slack conversation
A customer support team’s daily grind of pulling data, updating tickets, and chasing follow-ups across a Rails platform was collapsed into a conversational AI agent living in Slack.
Industry
B2B SaaS
Company Size
60 employees
Timeline
4 weeks
Tools Replaced
Manual workflows → 1 Slack agent
Before
- Support agents spent 2–3 hours every morning on repetitive tasks — pulling customer data, logging interactions, updating ticket statuses, and checking follow-up schedules across their Rails-based platform.
- Context-switching between the web app, spreadsheets, and Slack threads to piece together the information needed before every customer interaction.
- New agents took weeks to learn the internal tooling and the unwritten shortcuts the veteran team relied on.
- Management had no visibility into daily support activity without manually compiling reports at end of week.
After
- Custom AI agent embedded in Slack handles the entire daily workflow through natural conversation — pull a customer brief, log an interaction, update a ticket, queue a follow-up, all without leaving the channel.
- Agent connects to the existing Rails platform via new API endpoints, reading and writing data in real time with full permission controls.
- New agents productive on day one — the agent surfaces the right data and next steps without needing to know the internal tooling.
- Activity data captured passively through agent interactions, giving management real-time visibility into support volume and response times without extra reporting overhead.
2–3 hrs
Saved per agent per day
Slack
Single interface for daily tasks
4 weeks
End-to-end delivery
“The agent was ready before our API endpoints were. That tells you how fast Foxworks moved — we were the bottleneck, not them.”
— VP of Engineering
Built with
TypeScript · Slack Bolt SDK · Rails API integration · LLM orchestration · PostgreSQL
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