How IgniteTech Deployed AI Across 30+ Products the Right Way
An AI-first company with 19,200 monthly tickets and a $9.1M headcount problem solved it with disciplined, one-queue-at-a-time AI deployment.
Key Outcomes & Metrics
- 68% of tickets resolved autonomously
- $5.4M year-one P&L impact
- 73% faster resolution time
- 6.5x return on spend
IgniteTech runs 30+ enterprise products across supply chain, HR, communications, IT, customer experience, and sales. In 2023, leadership committed to becoming an AI-first organization, embedding AI across the portfolio and launching AI-native products. That pivot put acute pressure on support: 19,200 tickets a month, 30+ product lines, and distinct SLA and escalation requirements for each.
The Challenge
Scaling support the traditional way meant adding roughly 40 agents over 24 months at $88K fully-loaded each, about $9.1M in incremental spend. Support could not scale linearly while the company positioned itself as AI-first. The deeper risk was reputational: a public failure in AI-powered support would damage trust across the entire product portfolio at once. The fear was never AI itself. It was deploying it badly.
"We weren't afraid of AI. We were afraid of deploying it incorrectly. A failed AI support rollout would have damaged customer trust across our entire portfolio."
The Solution
IgniteTech deployed Kayako's AI agent through a controlled, queue-by-queue rollout rather than flipping it on portfolio-wide. The sequence was deliberate. First, define success metrics before a single ticket was processed: first-contact resolution, total resolution time, cost per ticket, CSAT stability, and autonomous resolution rate. Second, deploy in one high-volume queue with clear workflow boundaries and confidence thresholds set from day one, so any low-confidence ticket routed instantly to a human. Third, validate before expanding, and only extend to new product lines through the same gates.
Across the portfolio, the AI ran five capabilities in parallel: intelligent triage, autonomous resolution of routine requests, agent assist that drafted replies and surfaced knowledge, escalation intelligence that compiled full handoff summaries, and cross-product learning that carried resolution patterns from one queue to the next. Human fallback was embedded in every workflow, and SLA monitoring was live from activation. No rollout recorded a CSAT drop.
The Results
The pilot queue delivered within 90 days: autonomous resolution rose from 6% to 68%, average resolution time fell from 5.1 hours to 1.4 (a 73% reduction), first-touch resolution went from 56% to 84%, and cost per ticket dropped from $15.30 to $6.40. CSAT held steady at 91 to 92%.
Year-one financial impact reached $5.4M, a 6.5x return on Kayako's roughly $820K annual cost, made up of $4.8M in avoided hiring and $600K in operational efficiency, with break-even in month four. After the pilot proved out, IgniteTech standardized the same rollout model across all 30+ products, making AI performance predictable and repeatable rather than a bet.
About Kayako
Kayako is a complete, modern AI help desk platform. Run Kayako One as your full help desk, or deploy the Kay AI Agent into the help desk you already use. Either way, the entire implementation is led by our experts, so your AI is configured, trained, and tuned to succeed.
Support leaders partner with Kayako to scale customer support without scaling headcount, one queue at a time. Most teams are live in days, with 80% of repetitive tickets automated within 90, so cost per ticket falls while CSAT climbs.




