71% of tier-1 tickets, resolved by agents.
A Series D SaaS was watching support cost outpace ARR growth. Multi-agent orchestration with RAG over product documentation and CRM context inverted the slope in eight weeks.
Problem, strategy, implementation.
Inbound ticket volume scaled 1.6× year-over-year while ARR grew 1.3×. Per-ticket margin had inverted and CS hiring couldn't close the gap. Existing chatbots resolved less than 9% of contacts and degraded NPS when deployed naively.
Build a multi-agent system with explicit specialization: triage, retrieval, action and escalation. Ground every response in product documentation and CRM state. Ship behind feature flags with conservative confidence thresholds, then expand as eval scores held.
Two Ptimz engineers embedded with the support engineering team. Voice and chat surfaces shipped behind feature flags. Daily eval reviews with the CS leadership team. Full handover to in-house engineering by week eight.
Kickoff to compounding outcomes.
Discovery
Ticket taxonomy, intent mining, eval harness stood up against historical tickets.
Foundations
RAG over docs + CRM, tool layer, observability, guardrails.
Agent build
Triage, retrieval, action and escalation agents shipped behind flags.
Expansion
Voice surface, multi-language, confidence-tier expansion.
Handover
Runbooks, on-call rotation, and platform-team ownership.
Outcomes signed off by the client's CFO.
"We had two prior bot projects fail. Ptimz shipped multi-agent in eight weeks with NPS going up — not down. It is genuinely the first AI deployment our support team trusts."
What we actually built with.
Related case studies.
What could we ship for you?
A 30-minute session with the engineers who would lead your deployment. No slides, no sales — a working conversation.