You tried to make it work.
Really, you did.
You set up a Notion board called “Web Application Necessary Knowledge” and promised yourself this time it would be updated.
You spun up a Slack channel for triage that quickly became a dumping ground for despair.
You even told the client, with a brave face and a hint of optimism, that the support model was “evolving.”
But what you really meant was this: It’s broken. We’re just pretending. And hoping to toss the hot potato to a newbie before year-end.
Support is where optimism goes to die.
The devs who built the thing? Reassigned, resigned or spiritually relocated to other Jira boards.
The ones left behind have inherited the symptoms, not the diagnosis.
No history. No context. Just an error message and a hot-tempered client with a very short fuse.
And you can’t blame them. The clients I mean.
From their perspective, you’re the ones who built the plane. Why can’t you explain the turbulence?
Another ticket: “can’t log in – again!”.
No detail. No steps to reproduce. But a hair trigger to escalate.
You search.
You scroll.
You forage through DevOps like an urban fox desperately ransacking the bins for anything that smells like a precedent, or at least vaguely warm.
You find it: same issue, March 2023, closed. No root cause, no follow-up, no ceremony. Just crossed fingers and a production push.
This isn’t just inefficient. It’s absurd.
You’re burning engineering hours to repeat history.
You’re turning brilliant problem-solvers into very expensive librarians. With no filing system.
The tools you were sold don’t help.
Chatbots that can’t remember what you said five minutes ago.
Knowledge bases filled with articles from 2019, written in the tone of a hung-over SA on a PIP.
The industry doesn’t build for support. It builds for demos. Pretty interfaces. Precious little empathy.
And yet…
The idea of AI in support isn’t the problem. The problem is what they made it do.
AI shouldn’t deflect. It should remember.
Not impersonate your devs, but focus them on the true root cause.
Know the ticket history. Know what was tried. Know when not to ask again.
Deliver reassurance, not re-routing.
That was the shift.
We didn’t want automation. We wanted continuity. And laser guided accuracy. Something that could spot patterns not just keywords.
Something that could hold a thought longer than a chatbot with a head injury.
So we built Ovie. A technical support assistant for Optimizely customers.
Ovie learns from every ticket, every fix, every edge case.
It’s not perfect. But let’s be honest - support as a service is rarely covered in glory. It’s usually hidden in shame.
Ovie works because it’s designed for the real mess of post-launch life.
Most support teams are still trapped. Spiraling into technical debt and professional fatigue.
Support is penance.
Managed Service is marketing.
Support engineers spending 40% of their time being historians, 30% being therapists, and the rest firefighting without gloves.
We didn’t accept that.
We made a bet: what if support wasn’t a cost centre, but a lever? A way to clear the rot and finally talk about the future without dragging six months of unresolved bugs behind us.
Ovie is that bet.
An AI teammate that knows your mess and still shows up.
Not to replace people but to stop wasting their talent.
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