Introducing LaunchAI: A Smarter Way to Put AI to Work

Today we’re introducing LaunchAI, a new division of Slingshot that embeds a senior AI team inside your business to find and work through your AI priorities month over month. 

We built it because of what we kept hearing from our clients. From you. Over the past year, we’ve trained more than 250 people across a dozen organizations, and the same thing kept surfacing: the training wasn’t the only gap. People walked out knowing how to use the tools and still didn’t know where to point them. What they actually needed was someone who would go deep on their industry, their company, their specific pain points, and stay long enough to do something about them.

The Three Things We Kept Hearing

Strip away the industry details and nearly every one of those conversations reduced to the same three sentences, said almost word for word. We turned on the tools and nothing really changed. Our team loses hours every week to the same manual work. We know AI matters, and we have no idea where to start.

None of those are technology problems, which is what made them interesting. Chris Howard, Slingshot’s CIO, hears the first one most often, and his answer never changes.

“You don’t just turn on the tool and get the gain,” Chris said. “You take the tool, you go through the training and the pain of learning to use it properly. Your people were good at their jobs before. Now they’re good at their jobs using AI.”

That’s the part nobody budgets for. A license buys access the day you purchase it. The return shows up later, and only if somebody changed how they work to earn it. We assumed the larger organizations we trained had mostly sorted that out already. Most hadn’t.

“We realized we were doing things really differently than the people around us,” said Sarah Bhatia, Director of AI Product Innovation. “The gap across AI usage, AI understanding, and AI implementation is wider than almost anyone expects.”

People left our sessions energized, then ran straight into a Monday with no time, no plan, and no one to ask.

What We Built Instead

We wanted to give companies the thing we’d want ourselves. People who already know the tools, who take the time to learn your systems, and who don’t disappear when a statement of work runs out.

“LaunchAI is a new division of Slingshot,” Sarah said. “We’ve traditionally focused on building solutions for our clients. Over the last two years we realized we can provide a lot of value in a coaching and partnership role as well. It’s never been harder to stay on top of tech than it is right now, and staying on top of it is our full-time job.”

You get the same people throughout, so context builds instead of resetting. They learn your constraints and why that one process still eats half of somebody’s week. You also direct the team, and the mix shifts as your priorities do, moving from training to building to roadmapping without renegotiating anything.

That’s the investment case. You aren’t buying hours. You’re buying a team that becomes more valuable every month it stays.

What the First Ninety Days Look Like

LaunchAI runs as an ongoing partnership, but the first three months have a deliberate shape. The first two weeks belong to us.

“We get into your business, understand your processes, your pain points, how you actually operate,” Sarah said. “Then we work together to turn those into opportunities.”

Picking where to start isn’t as scientific as people expect. Chris points teams at whatever they hate doing most. That’s where people are most willing to try something new, because they can already see the hours coming back. You’ll have something in hand before day 30. Usually that’s a working session on one problem area. Sometimes it’s a small skill built in Claude or whichever platform your team already uses.

Through the second month the rhythm settles. We build, your team uses it, we adjust. Adoption gets as much attention as the building does, because a skill nobody opens is worth nothing. QA analysts who spent years verifying releases by hand start writing automated tests with AI instead.

“Not just using AI, but using AI to create the tools they use every day,” said Doug Compton, Director of AI Engineering. “Things that were too expensive before, or that the IT department never thought were worth their time, they can now build themselves.”

By the third month the work stops being a collection of fixes and starts changing how whole groups operate.

“It’s about cognitively offloading the repetitive work that doesn’t need a human perspective,” Sarah said, “so it frees your team up for the work only your people can do.”

The subtler shift is judgment. Chris sees clients spotting opportunities they’d have walked right past on day 30. At ninety days you decide whether to keep going, and from there it runs month to month.

How the Work Compounds

Most of the value shows up after the first term. The LaunchAI team knows your systems, your people already use what got built, and requests that sounded unrealistic in month one look obvious by month six.

Getting there depends on people more than platforms. Sarah looks for the tinkerers, the curious ones who carry the initiative from inside, and turns them into the people everyone else asks for help.

One of our favorite success stories is Louisville Water. Their Business Innovation team collaborated with our LaunchAI crew to solution, build and launch two new products in the first 90 days. Their internal team upskilled fast enough that they now look at a business problem with the skill set and confidence to solve it themselves.

“They’re really able to tackle a business problem and say, let’s just build a custom solution, and then go do it,” Sarah said. “Their team is getting upskilled so quickly in how to engage with these tools, and they’ve got us backing them up for the more complex technical pieces.”

That’s the outcome we’re building toward. Not a client who needs us for everything, but one who needs us for the hard parts and handles the rest.

Why We’re Doing This

We trained a few hundred people, listened on the way out, and heard the same problem described a dozen ways. Licenses everywhere, value almost nowhere, and the work that closes that gap too small and too constant for any project to hold. So we stopped trying to scope it and built a team instead.

If you’re somewhere in that gap, start with a conversation. No commitment, just a real look at where AI could take your business next.

We spent two years learning this the hard way. What you build with it is the part we’re excited to see.