Case 02
AI Support Agent for a High-Growth D2C Brand
High-growth D2C consumer brand · 1.5 months
98%first response under 24 hrs, from 82% · 74% of replies sent unedited
Where it stands
Live and in use- 74%of replies sent without a human in the loop
- 82% → 98%first responses within 24 hours
- ~70%less handling time per support email
The challenge
A direct-to-consumer brand was growing at roughly 30% month-on-month, and its support inbox was scaling just as quickly. Agents spent about eight minutes on an average email, while a large share of inbound mail was not a customer request at all: promotional messages, vendor outreach, and billing reminders still had to be opened and triaged.
What we built
03 parts- 01
AI support agent
Built an agent that classifies inbound email, filters non-support messages, identifies the request type, and generates the appropriate customer response.
- 02
Workflow logic, guardrails, and evals
Mapped support SOPs into explicit workflows and built a labelled evaluation dataset before tuning the agent to production accuracy targets.
- 03
Production monitoring
Added reviewer checks and live monitoring so new edge cases could be identified and corrected after rollout rather than discovered through customer complaints.
The results
- 74% of replies are sent without a human in the loop.
- First responses within 24 hours improved from 82% to 98%.
- Average handling time reduced by roughly 70%, from 8 minutes to 2-3 minutes.
- The automation offset the need for approximately two additional support hires.
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