Support AI that closes tickets, not just deflects them
Most 'AI support' is a chatbot that links to your help center and hopes. Rymiq agents actually do the work: process refunds, update orders, reset access — inside your systems, under your rules.
Deflection is not resolution
The support industry has spent a decade celebrating 'deflection' — a metric that counts a customer giving up as a win. A customer who reads a help article and leaves without answering 'did this solve your problem?' counts as deflected. Solved? Nobody knows.
Rymiq measures resolution instead: the ticket is closed, the action was taken, and the customer confirmed it or stopped writing back because the thing actually got fixed. Across our deployments, support agents resolve a median of 80% of inbound volume across chat, email and voice — with resolution audited, not assumed.
The difference isn't better conversation. It's authority. Our agents connect to your order system, billing platform and identity provider, so 'where is my order?' gets a tracking link, 'I was double-charged' gets a refund within policy limits, and 'I can't log in' gets a verified reset. All logged, all reversible, all within limits you set.
How it fits your existing support stack
Rymiq sits inside the tools you already run, not beside them. The agent works your Zendesk, Intercom, Freshdesk or Salesforce queue like a staffed seat: it picks up tickets, resolves what it can, and assigns the rest to the right human with a diagnosis already written.
Your macros, your tone guide, and your escalation matrix become the agent's operating rules. If your policy says refunds over $200 need human sign-off, the agent prepares the case and routes it for one-click approval rather than guessing.
Chat, email, voice and WhatsApp handled by the same agent with the same knowledge
Full conversation history and CRM context on every interaction
Draft-mode option: the agent proposes replies and a human approves, until you trust it to send
Every action logged with a before/after diff your QA team can audit
The numbers that move
First response time is the headline: from hours to under 10 seconds, around the clock. But the metric your CFO will care about is cost per resolution, which typically drops 60–75% on automated volume. And the one your support director will care about is what happens to the humans: they stop doing password resets and start handling the genuinely hard cases — which is also why attrition on support teams tends to fall after deployment, not rise.
Customer satisfaction usually holds or improves, with one consistent pattern: CSAT on AI-resolved tickets is highest when escalation is instant and unconditional. Customers don't resent talking to an AI. They resent being trapped with one. We design for the exit as carefully as the conversation — read how it works in the customer stories.
When should you not automate support?
Honest answer: if your volume is under roughly 500 conversations a month, the math rarely justifies a platform — a good shared inbox and a well-written FAQ will serve you better. And if most of your tickets are genuinely novel (custom enterprise deployments, complex claims), aim for AI-assisted humans rather than autonomous resolution: the agent drafts, your experts decide.
Everyone else — the companies drowning in 'where is my order', 'how do I cancel', 'can you resend the invoice' — is leaving money and staff sanity on the table every month automation gets postponed.
Frequently asked questions
See it resolve one of your real tickets
Bring three of your actual support tickets to a demo. We will configure an agent live and show you what it resolves, what it escalates, and why.