In this episode of the Sunny Ray Show, host Sunny Ray talks with Mark Barber, co-founder and CEO of Ear Mark, an AI workspace that turns live meeting conversations into finished work in real time, such as requirements, tickets, and updates. Mark explains how Ear Mark differs from generic AI note takers by producing usable deliverables during the conversation rather than summaries created after the fact. He traces the company's origin from his prior roles running engineering at Mindbody and co-founding Product Plan, a SaaS platform for product managers that was later acquired. Mark shares how the idea evolved from an early Vision Pro speech coaching concept into a botless, platform agnostic productivity tool built for product and engineering teams. The conversation covers distribution through founder led sales, trust building through reliability and privacy, cost engineering for AI inference, and how offloading routine deliverable creation frees product managers to focus on higher value work. The episode offers a candid look at building an AI native company from idea to product market fit.
Ear Mark's Mark Barber explains how AI can turn live meetings into finished work instead of just notes.
What is Ear Mark?
Ear Mark is a productivity suite where the work completes itself. It listens to meetings in real time and turns what is said into finished work like requirements, documents, tickets, updates, and next steps. Unlike generic AI meeting tools, it lets product teams move forward without extra manual synthesis afterward.
What were you doing before Ear Mark, and what did that chapter teach you?
Before Ear Mark, my co-founder and I spent six years at Product Plan, a SaaS platform for product managers, and before that we ran engineering at Mindbody, a large enterprise wellness SaaS company. At Mindbody I had over 300 reports and saw how much time meetings consumed with little value created, teaching us how broken and coordination heavy meeting culture really was.
When did you first realize meetings were such a broken workflow?
We always knew innately that meetings were low value activity, but many of us feel powerless to change the rituals and coordination overhead expected of us. The epiphany came with modern LLMs and generative AI: we realized we could take the drudgery out of these roles and build the tool we always wanted for people like us.
What felt most risky when you decided to start this company?
Since we are both older founders with families, giving up a stable paycheck was risky. Also, our first solution attempt was actually a Vision Pro product for immersive real time speech coaching, which we spent months building before the Vision Pro team did not materialize, pushing us to pivot to a web based, then real time work automation solution.
Why does invisibility win over flashy AI demos, and where is the proof in your data?
People often build brittle DIY AI workflows that break with model or agent updates, so we wanted to remove that fragility entirely by making Ear Mark extremely reliable, low latency, and easy to launch with one click across any meeting platform or face to face. Users report saving about five hours a week, and our DAU to MAU ratio is around 40 percent, close to consumer grade engagement.
How do you win the distribution game for an enterprise AI product?
We rely heavily on founder led selling and LinkedIn outbound. Typically one or two PMs in an organization adopt the tool, then sell it up to a director for a broader evaluation and a 30 day pilot, during which we align legal, procurement, and security, and define clear success criteria that usually lead to a go decision.
How much of building an AI company right now is a cost engineering game, given inference dropped from 70 dollars a meeting to under a buck?
It is a huge part of it. We intentionally absorb higher costs early to build ahead of where frontier models are going, then rely on our multi agent architecture to map specific artifacts to cheaper models or throttle the experience when needed, giving us sensible levers to control costs without hurting the business.
When meetings produce the ticket, spec, and update automatically, what does a product team stop doing and what do people move up to?
Product managers currently spend most of their time close to their own teams creating deliverables due to proximity bias, which consumes their cycle time. When Ear Mark handles a large portion of that deliverable creation automatically, it frees people to focus on the higher value parts of product management they originally got into the role for.
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