Support Deflection Agent for a Series D SaaS Platform
Illustrative reference architecture. This is a composite engagement template built to show how Mopshy structures enterprise work. It is not a real Mopshy client, and every figure, KPI, and quotation on this page is illustrative rather than measured client data.
Retrieval-grounded support agent, in-app copilots, and an internal knowledge assistant — deployed across product, support, and success teams.
63%
Tier-1 deflection
+14 pts
CSAT
−28%
Support cost per customer
The bottleneck
Support headcount growth outpaced ARR growth. CSAT under pressure. Product docs, changelog, and Zendesk macros lived in three disconnected systems.
The system
- Retrieval-grounded support agent with source citations and confidence gating
- In-app copilot answering how-to questions in product context
- Internal knowledge assistant for support + success teams over docs + tickets
- Weekly evaluation harness scoring hallucination, coverage, and CSAT proxy
Outcomes measured, not promised
8,400
Customers served
<3s
Median agent response
97%
Answer-with-citation rate
0.4%
Hallucination rate (evaluated)
What it cost, what it returned
Investment
$1.9M program (year one)
Payback
5 months
Annualized value
$11M support cost avoidance
How it is built
- Docs + changelog + Zendesk knowledge unified in a retrieval index
- Confidence-gated support agent with human handoff
- In-app copilot invoked via product context
- Evaluation harness with weekly regression tests
Representative engagement. This case study describes a composite of Mopshy AI's enterprise engagement patterns, delivery methodology, and observed outcome ranges. Company names, individual quotes, and specific figures are illustrative and used to communicate the enterprise pattern rather than to describe a single identified client.
30-minute working session
Find the highest-ROI automation in your business
Bring one workflow that is slow, repetitive, or leaking opportunities. We will map the bottleneck, the systems involved, and whether automation is actually worth implementing.
No obligation. If automation is not the right answer, we will say so.