Open the channel.
Talk to Stefan. Tell him what you do. He'll show you where AI agents would carry the most load in your operations, with a concrete recommendation and rough numbers.
Stefan reads the signal.
Stefan is the lab's frontline analyst. Tell him what your business actually does and where the friction sits. He'll surface the three or four spots where AI agents would carry the most load, with a concrete recommendation, rough numbers, and what implementation would take.
When the question moves past him (a custom pilot, pricing, a deeper architecture conversation) he hands the thread to the team with the context intact, so you never have to re-explain your operations.
Four reads, on the line.
Stefan is calibrated for the analysis visitors actually need, operations in, a recommendation out. The rest gets routed to the team.
Where agents fit
Tell Stefan what your operations look like and he will surface the three or four spots where AI agents would carry the most load, ordered by payoff.
What kind of agents
From the leverage points, a concrete read on which agent patterns fit (intake, routing, classification, drafting, reconciliation) and how they would connect to your existing stack.
What it would take
A rough estimate of implementation complexity, integration surface, and timeline, the kind of numbers you would want before a call with the team.
Routing to the team
When the question moves past Stefan (a custom pilot, pricing, a deeper architecture call) he hands the thread to the team, with the context intact.
The overlap is real. Make contact.
Open the channel. Tell Stefan what your operations look like. He'll show you where AI agents would carry load, and what implementation would take.