Automate · Build the case, then the bot
We don't sell you a bot. We make sure your operation deserves one.
Automate is an AI agent build for a support operation that already exists. We rebuild the help center so a model can actually retrieve from it, map your real contact reasons, design the escalation paths, and then build the bot on top of all three.
The audit tells you whether you're ready, and that verdict is included in it. If you're not, we'll say so before anything gets built.
6 to 12 weeks
Readiness confirmed to bot live
Fixed price to build
Ongoing tuning runs through Operate
Readiness gated
If you are not ready, we say so before anything gets built
What this has actually done
~15%
of incoming ticket volume deflected
At 12,000 tickets a month and an 8 minute average handle time, that's about 240 hours of agent time back every month. The same readiness-first process caught real documentation and workflow gaps at PDI and Groupize before either bot got built.
AI deflection engagement, single client
Your number will be different, and that's the point.
Deflection depends on your contact mix, not on the model. Plenty of your top contact reasons need account access, judgment or an exception, and no bot should be attempting those.
The AI Deflection Model sizes what's genuinely answerable in your queue from a real sample of your tickets, and builds the cost per contact and ROI case that leadership asks for before approving anything. It's quoted in your audit readout.
It starts with the auditThe question everyone asks first
Why not just turn on the AI your help desk already ships?
You can, and the setup takes an afternoon. We're not going to pretend otherwise. Here's what the setup doesn't cover.
The vendor gives you a model. Nobody gives you the content.
Every AI agent answers from your help center. If your articles were written to document a policy rather than answer a question, the bot inherits that and gets it wrong confidently.
The vendor does not know which questions are answerable.
Plenty of your top contact reasons need account access, judgment or an exception. Pointing a bot at those produces an escalation with extra steps and an annoyed customer.
The vendor cannot tell you what it will deflect.
Containment rates in a sales deck come from somebody else's operation. Yours depends on your contact mix, and that is a question about your tickets, not about the model.
The vendor is not there in month three.
Contact reasons shift. A bot nobody tunes quietly degrades, and the first sign is usually a CSAT drop nobody connects to it.
None of that is a criticism of the software. The models are good. The part that decides whether yours works is the operation underneath it, and that is not something a vendor can sell you.
What gets built
Six things, in this order. Not bot first.
Help center rebuilt for retrieval
Articles rewritten answer-first, one clear answer per question, structured so a model can actually retrieve them. This is most of the work and it is why most rollouts fail.
Intent and contact reason mapping
Your real contact reasons mapped to what the bot should attempt, built from your tickets rather than from a template taxonomy.
Bot build and training
Configured on the cleaned up content, on whatever platform you are on or moving to.
Escalation design
Every question the bot should not hold has a defined human path, decided before launch rather than discovered by a customer.
Deflection reporting
Containment separated from abandonment, so you can tell a question answered from a customer who gave up. Most dashboards cannot.
A tuning cycle
Monthly review of what it missed and what it should not have attempted, feeding back into the content.
How it actually runs
Five phases. Same order, every build.
The first one is already done by the time you get here. That's what the audit was.
Investigate
Already done. The audit gave you the readiness verdict, and the Deflection Model sized what is worth automating.
Intent
We agree what the bot handles and, more importantly, what stays with a human.
Implementation
We rebuild the knowledge base, then build the bot on top of it rather than around the mess.
Instructional design
Training gets rebuilt wherever the bot draws from it, so the answers it gives are correct.
Integrate
It goes live while we watch performance and tune, rather than walking away at launch.
Automate retrofits. Launch builds native.
Automate adds AI to an operation that already exists, once the audit confirms it deserves one. If you have no support team at all, a Launch build designs the AI layer into the operation from the start, because there's no pre-AI process to retrofit.
See how Launch worksA bot nobody tunes degrades quietly.
Contact reasons shift, and the first symptom is usually a CSAT drop nobody connects back to the bot. The first tuning cycle is part of the build. Ongoing, that runs through Operate.
See how Operate works13 consecutive 5 star Clutch reviews, across ecommerce, healthcare, nonprofit and retail. Read the case studies →
WHO'S ACTUALLY DOING THIS
I'm Ty Givens. 25 years running support operations at See's Candies, Thrive Causemetics and Intuit before starting CX Collective. I lead every engagement, and my team does the hands-on delivery. That's the whole pitch.
25 years in support operations
Questions we get
Before you buy a bot.
Why not just turn on the AI our help desk already ships?
You can, and the setup takes an afternoon. The reason it usually disappoints is that the bot answers from your help center, and most help centers were written to document policies rather than answer questions. The model is the easy part. The content, the contact reason mapping and the escalation paths are the work, and no vendor does those for you.
How do we know it will actually deflect anything?
You do not, until somebody looks at your tickets. Containment rates in a vendor deck come from someone else's contact mix. The AI Deflection Model sizes what is genuinely answerable in your queue, without account access, judgment or an exception, and prices what that is worth. It is quoted in your audit readout.
Can we buy Automate without the audit?
No. Automate is scoped from what the audit found. Building a bot before anyone has checked whether the documentation can feed one is the single most common way these projects end up switched off in month two.
What if the audit says we are not ready?
Then we say so, and you have saved yourself a build. Usually the gap is documentation or contact reason definitions, which is Scale work, and Automate follows once it is fixed. We would rather tell you that than sell you a bot that embarrasses you.
How is this different from the AI layer in a Launch build?
Automate adds AI to an operation that already exists, after the audit has confirmed it deserves one. A Launch build is for a company with no support team at all, where the AI layer gets designed into the operation from the start because there is no pre-AI process to retrofit. Same discipline, different starting point.
Who tunes it after launch?
We do for the first cycle, and the tuning cadence is part of the build. Ongoing, that lives in Operate. A bot nobody tunes degrades quietly as contact reasons shift, and the first symptom is usually a CSAT drop that nobody connects back to it.
Find out if you're ready before you build one.
Two weeks inside your operation, a scorecard across five areas, and a straight answer on AI readiness. The fee comes off whatever you decide to build.