Close support tickets end-to-end.Even the ones your current AI can't.

Out-of-the-box AI reads your help center. That's it. It can answer "what's your return policy" but fails on anything that needs real context, account history, contract details, edge cases. We integrate with your helpdesk, CRM, product data, and actual resolved tickets. That's why our resolution rates are typically 2–3x higher on tickets that require context, not just copy-paste answers from docs.

Every reply is confidence-scored before it goes out. Below your confidence threshold, the ticket is drafted for human review, not sent autonomously. We also run simulations on your real ticket history before go-live, so you see where the model is solid and where it isn't, by topic, by customer tier, by language. If it doesn't know, it escalates. It doesn't guess.

Yes, down to the individual ticket type. You set escalation rules, confidence thresholds, tone guidelines, and policy boundaries. Shadow mode means we draft, your team approves. Autonomous mode means we close, your team reviews afterward. You move each category from shadow to autonomous when you're ready, not before.

About two weeks end-to-end. Week one is integration and simulation on your past 90 days of tickets, you see projected resolution rates before anything goes live. Week two is shadow mode with your team reviewing every draft. Autonomous resolution on low-risk categories usually starts by week three, higher-risk categories later as trust builds.

SOC 2 Type II in progress, EU data residency available. We sign DPAs as standard, and customer data is never used to train foundation models. Ticket data stays in your tenant, our learning loop is customer-specific, not pooled.

You could. The hard parts aren't the LLM calls, they're the context pipelines, the edge-case handling, the confidence calibration, the simulation framework, and the feedback loops that make the system actually improve over time. That's 9–12 months of focused work before you'd match what we ship today, and we keep improving every week. Your engineers have higher-leverage things to build.

We scale with your volume automatically. Black Friday, product launches, outages, there's no capacity ceiling and no overtime cost. You pay per resolved ticket, so the economics actually get better during spikes, not worse.

Then we don't charge for it. Unresolved tickets go to your team with full context attached, what we tried, why we escalated, what the customer needs. Your agents start from minute 10 of the investigation, not minute zero.

Yes. Run a simulation on 90 days of your past tickets. You get a report showing projected resolution rate by category, flagged edge cases, and knowledge gaps we detected. If the numbers don't justify the investment, you walk away. No contract, no setup cost for the simulation.

Yes, 80+ languages out of the box, including German, French, Spanish, Portuguese, Italian, Dutch. Your customers write in their language, we reply in their language. Trained on your actual multilingual ticket history, so tone and terminology match your brand, not a generic translation.

We work best with teams handling high-volume, context-heavy support, energy, telco, fintech, e-commerce, insurance, SaaS. If your tickets require pulling data from multiple systems (CRM, product, billing, contracts) before a reply makes sense, we're built for you. Pure FAQ-style support is less of a fit, off-the-shelf tools handle that fine.

A ticket counts as resolved when it's closed without reopening within X days. If a customer writes back dissatisfied and the ticket reopens, we don't charge. That's the commitment, you pay for outcomes, not attempts.