Casa Auto Group’s VP of Digital Operations, Jarrod Kilway, is proving that AI in dealerships doesn’t have to be complicated or risky.
Driving the news: Instead of buying another off-the-shelf tool, he built a secure, private GPT that gives his general managers real-time answers from the group’s own data.
He did this by wiring together Casa’s DMS, CRM, inventory, Google Analytics, and paid media results inside an AWS “data clean room.”
He then connected it to GPT through an API (a secure bridge between systems).
The result: Managers type a question (bounce rate, lead close rate, ad spend efficiency) and get answers in seconds.
“The main problem really looking to solve is the ability for the general managers to take action and take action quickly,” Kilway told Daily Dealer Live hosts Sam D'Arc and Uli de’ Martino.
Jarrod Kilway
“Without having to necessarily call me or send me an email or jump on a Zoom call, it’s the ability to give them, in essence, a jar in a box that can answer a question,” he said.
Why it matters: Dealers are buried in tools, but most of the data lives in silos. That’s why Kilway’s goal was to make his team’s existing data usable.
Especially because, as he points out, public AI comes with its own risks.
“Everybody on the call, don’t go take your financial statement or extract all your customer lists and run it into ChatGPT,” he said. “Because there are smart people…who could go and extract that through queries because that is open and public at that point.”
That’s why, by isolating Casa’s data in a private environment, managers get the insights without risking exposure.
What this looks like in practice: Kilway said each store has a secure login that looks like ChatGPT, preloaded with the most common questions GMs ask.
For example, he said he asked the question: “What’s our close rate on leads older than 21 days?”
The system answered 2%, a number he shared that would’ve taken hours in Excel.
From there, he drilled down into which lead sources dropped off, turning raw data into a conversation about people, process, or provider.
“In the past, I’d sit there for an hour or two hours in Excel trying to configure everything dialed in,” he said. “It now results in a matter of a minute.”
On costs: Kilway revealed that building the system took about $1,000 upfront, with a monthly cost of $800–$1,200, depending on API usage.
To his point, that’s a fraction of the $4,000/month contracts some dealers sign for tools they don’t fully understand.
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Regarding obstacles: Kilway says the biggest lift was “mapping fields,” or teaching the system that the first name in one database equals the customer name in another.
Even still, after 30–45 days of training, he said accuracy improved enough that he now only checks for errors once a day.
“I look at that as my job,” Kilway said. “I’m the Brinks armored truck driver of the dealership, and nobody’s getting into it.”
Looking ahead: Kilway said the next step is rolling the system up to the group level, so executives can see performance across rooftops in one place.
After that, Casa’s e-comm team will start using it to keep daily operations accountable.
Long-term, he also wants to plug in F&I lender documents so the tool could actually recommend which bank to send a deal to based on a customer’s profile and profitability.
And if he had one do-over?
“I wouldn’t have waited,” Kilway said. “If you’re thinking about it, start now. Make a plan, draw a plan out of where you want this to be in a year, and try to get from one year to six months.”
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