Anticipated Objections
Questions VCs will ask, and how we think about them.
The 7 Core Questions
| Question | Our Stake |
|---|---|
| Market | Healthcare back-office is massive. AI + expert services will restructure it. |
| Timing | AI crossed a threshold, but you need healthcare depth to apply it. Window is now. |
| Team | Rare bridge — we understand healthcare economics AND we can build. |
| Traction | Premera contracting. Real pipeline. Healthcare-slow but moving. |
| Insight | We see the real problems (incentives, relationships), not just symptoms. |
| Path | Land on use cases, prove value, expand. Services + AI scales better here than pure SaaS. |
| Risk | We know the risks. We're not naive. |
Market Questions
"Is the market big enough?"
Healthcare back-office is massive and broken. Utilization management alone is a multi-billion dollar function across payers. The broader thesis: AI + human expertise will restructure how healthcare administrative work gets done. This isn't a feature — it's a platform shift.
"Isn't healthcare slow/hard to sell into?"
Yes. Sales cycles are long. But that's a feature, not a bug — it creates stickiness. And we're seeing real engagement: Premera is contracting, not just having exploratory calls. Movement is real, even if pace is healthcare-speed.
"What about regulatory risk?"
We're building with compliance in mind. The regulatory landscape is evolving, but our approach (augmenting humans, not replacing them) aligns with how healthcare wants AI applied. We're not making autonomous clinical decisions.
Competition Questions
"What about [incumbent]?"
Incumbents like Epic don't understand AI the way we do. They move slow. They're optimized for the old world. We're building for the new one.
"What if [big tech company] does this?"
Big tech doesn't understand healthcare. They've tried. They've failed. The domain expertise required is real. We have it.
"How do you win against better-funded competitors?"
Most competitors fail because they don't understand healthcare. Money doesn't fix that. We win on insight, not capital.
Technical Questions
"What does the product actually do?"
We're AI-native. Vibe coding makes it possible to build whatever customers need, fast.
We start from first principles every time. We work with customers to customize for their workflows. What that looks like varies — could be a UI, could be backend software, could be automation running in the background. The customer's workflow determines the form.
The first wedge: Inpatient Status Assessment
When a patient is admitted, someone decides: inpatient or observation? This decision happens at T+4-8 hours — but no one applies criteria at that moment. Physicians decide without Two-Midnight guidance. Case managers review 14-24 hours later, after the decision is locked.
We built decision support that brings criteria-based reasoning to the decision point:
- Pulls clinical data automatically (vitals, labs, diagnosis)
- Applies Two-Midnight reasoning
- Produces structured assessment: what supports the status, what's missing, what to document
- Transparent reasoning, not a black box
Why this wedge works:
- Concrete pain: $2K-$5K revenue difference per case
- Tractable: Two-Midnight provides a specific question AI can answer
- Differentiable: Not InterQual/MCG — automated, prospective, transparent
The bigger point: We're creating generalizable, scalable things through customer work. Each engagement teaches us what to productize. This wedge proves the model; adjacent UM workflows follow.
"What's the moat? Isn't this just a wrapper?"
The moat isn't the model — it's understanding where AI helps vs. creates liability. That requires healthcare depth. Our combination of healthcare PE and engineering is rare and not easily replicated.
Also: the partnership. Two people who trust each other, think together, have complementary access to different worlds. That's real.
And: the ability to teach. We're not just building for customers — we're elevating their people into AI-native builders. That's stickier than any software.
"How does AI accuracy matter here?"
It matters a lot. Healthcare tolerates less error. Our approach: augment humans, don't replace them. AI handles the grunt work; humans make the judgment calls. That's how you build trust.
"What happens when models commoditize?"
The model is one input. The real value is knowing how to apply it — which workflows, which edge cases, where the liability is. That knowledge compounds. It doesn't commoditize.
Team Questions
"Do you have healthcare experience?"
Yes. Healthcare private equity background means deep understanding of economics, incentives, organizational dynamics — not just surface knowledge. And we can build. Engineering + healthcare PE is a rare combination.
"Why are you the right team?"
We bridge the gap that kills most healthcare startups. Tech people don't understand healthcare economics. Healthcare people don't understand technology. We have both.
Traction Questions
"Why isn't there more traction yet?"
Healthcare moves slow. But we have real engagement: Premera contracting (major health plan), AppriseMD late stage, growing pipeline. This is early-stage traction in a long-cycle market.
"What's the sales cycle?"
Months, not weeks. That's healthcare. But once you're in, you're in. Stickiness is high.
Business Model Questions
"How do you make money?"
AI + expert services for health plans. Recurring revenue from ongoing engagements.
"Services vs. SaaS margins?"
This is a red herring at N=1. Here's the real question: If 80% of healthcare organizations are going to be AI-enabled, who does that work?
We're doing the McKinsey work — strategy, thinking through the problem. We're also doing the Palantir work — building the software, running parts of the business.
Services come first: identifying, consulting, problem-thinking. Software emerges when you create repeatable processes. You can't have repeatable abstractions at N=1. That's impossible.
What you need is tight integration between business and technology. Not siloed thinking. The founders who can hold both in the same mind are the ones who can create stable abstractions over time. That's us.
"What's the pricing power?"
We solve expensive problems. Utilization management is a cost center for health plans. If we make it work better, there's clear ROI. Pricing follows value.