Sep 3, 2026 earnings call — Gartner recognition and AI customer shift
AI customer revenue grew 20% year-over-year, and total revenue was $91.1 million for fiscal 2026.
Revenue $0.0B (est $0.0B) · EPS $0.08 (est $0.03)
Key quotes
"In July this year, Gartner published its first ever Magic Quadrant for customer service knowledge management systems and named eGain a leader, positioned highest for ability to execute and furthest for completeness of vision."
"AI customer ARR increased 13% year-over-year and represented 72% of total SaaS ARR at year-end."
"The first was the eGain IVA, which is an intelligent voice agent. What's unique about it is that it is using the same trusted knowledge platform as we use for all our digital self-service tools."
Analyst Q&A 2
non-AI revenue and AI pricing impact
Q (Vijay Homan · Craig-Hallum): He asked when the company plans to run off the non-AI ARR and how profitable those businesses are. He also asked whether AI is causing pricing pressure now or later, and what will drive future growth (price, new customers, seats, or churn).
A: Management said the non-AI business is expected to go to 0 by 2030 and they hope to convert some into AI. They said they are seeing some pricing pressure but also creating new AI product revenue, and expect about "1 or 2 points" pressure over the next "2 to 3 years". They said most growth will come from new logo acquisition, not from moving legacy customers.
"But from a modeling standpoint, we'd expect that to be to 0 as we get to the 2030 time frame." — Eric Smit (CFO)
using many AI models and costs
Q (B. Riley): He asked whether using an ecosystem of many AI models (not just one) increases demand for a knowledge management solution. He also asked if this dynamic is different for big frontier models versus open source models.
A: Management said being precise about what you feed into models cuts AI token costs a lot — sometimes by a factor of 10 — and that this makes their knowledge management important. They also said they use the right model for each task to manage costs, and that frontier models only have about a "10% to 15%" quality edge while cost differences can be a factor of "10", so smarter routing will be needed as real-time usage grows.
"And what we see with our approach to it is just by being sharper in what you are feeding into these AI tools, you can keep the costs down significantly, sometimes by a factor of 10." — Ashutosh Roy (CEO)