AI & Automation Solutions
A human centered approach
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You already know what the problem is.
Maybe it's a workflow that eats hours every week. A process your team has worked around for so long it just feels normal. Or something you've tried to solve with existing tools and none of them quite fit.
That's exactly the kind of problem I build solutions for.
Off-the-shelf tools are built for general problems. Most teams have specific ones.
There's a gap between what an existing tool does and what your team actually needs. That gap is where the frustration lives. You adopt a new platform, go through the implementation, train everyone on it, and still find yourself working around the parts that don't fit. Or building manual processes to cover what the tool can't do.
The problem isn't the tools. Most of them are good at what they're designed for. The problem is that what they're designed for isn't quite what you need.
That's the gap I build into.
How Works
it
Before I build anything, I gather requirements. Thoroughly.
This is where most solution projects go wrong. Requirements get skipped or rushed, and the team ends up building something that solves a simplified version of the problem instead of the actual one. I've seen it happen enough times that I treat this step as non-negotiable.
I start with a stakeholder conversation to align on goals, define what success looks like, and establish how we'll know when we've gotten there. Then I go deeper. Multiple conversations with the people who actually have the information, not just the people who commissioned the work. I'm listening for the edge cases, the exceptions, the things that would break a generic solution.
That process also tends to surface what's hiding underneath the original request. Data issues. Process gaps. Risks that need to be addressed before anything gets built. Finding those early is what keeps the project from going sideways later.
Once requirements are clear, I build. Engagements range from four weeks for simpler solutions to six months for more complex ones. Scope drives the timeline, and scope gets defined during requirements gathering, not before.
I focus on team productivity solutions. The work is internal, built for the people doing the work every day.
Custom GPTs
Trained around your team's specific context, language, and workflows. Not a generic assistant. Something that actually knows how your team operates.
Automated Workflows
Repetitive manual work that runs on its own. The tasks that eat time every week without adding any real value.
Integrations
Connecting the tools your team already uses so information stops falling through the gaps between them.
AI Agents
Built to handle specific tasks or support specific roles. Designed around what your team actually needs to get done.
“I had been feeling so burnt out with my content and literally one session with Athena changed everything.
I'm baby organic authentic skateboard microdosing waistcoat, vinyl sartorial. Bodega boys street art four dollar toast.
— JEN OLMSTEAD
Expand What You’re Capable Of With AI
A process that took 40 hours now takes 4.
That's not a hypothetical. It's what happens when a solution is built around how a team actually works instead of how a vendor assumes they work.
The work that used to pile up runs on its own. The manual steps that required someone's attention every single day stop requiring it. And the people who were spending their time on that work get it back to spend on something that actually matters.
That's what a solution that fits looks like in practice.