The problem
HelioMed sells into hospital procurement and clinical-engineering teams, an audience where an automated or generic-looking message can cost a relationship before it starts. The company's compliance function also needed to be able to reconstruct, for any prospect, exactly what had been sent and by whom.
Existing outbound tools the team had trialled leaned on browser extensions or shared credentials to automate LinkedIn actions - a non-starter for a team that needed every action traceable to a specific, accountable person.
What they configured
HelioMed kept every outreach step human-assisted: connection requests, engagement and message sending are performed by the five owners from their own accounts, with no bot and no shared login. The scoring model raised the AI / digital transformation fit weight, since HelioMed's differentiator was implementation speed for hospitals mid-way through a digitisation programme.
Round-robin distribution spread the 1,150-prospect import evenly across the five owners, each capped at a daily limit that matched realistic manual capacity rather than what a fully automated tool could theoretically push.
What happened
Every score, owner assignment, generated message and classified reply was written to the activity log with a timestamp and an actor - a compliance review that used to mean reconstructing an inbox from memory became a straightforward export.
Because nothing sent automatically, the sales cycle didn't get faster in the way a fully automated platform might promise - it got more defensible, which was the actual constraint HelioMed was solving for. Reply intelligence still did its job: a neutral reply from a hospital contact went back into the pool rather than being marked as a lost cause.