Answer Gaps
Where our investor answers are weak, with suggested improvements.
Last updated: 2026-02-19 Calls analyzed: 8 (added Wavemaker 360 2/19)
Priority Gaps (came up, answered poorly or thinly)
1. Scalability — redeployable tech vs. custom consulting
Came up in: Refract VC (2/5), NextGen VP (2/5), Tau Ventures (2/6) Frequency: 3/6 calls — the most asked question
What happened:
- Refract: Caesar asked directly. Thomas said "we want to be more the former" but couldn't name redeployable components.
- NextGen: Deborah asked the pointed version: "Is there a roadmap to decreasing services? Or are we investing in a tech-enabled consulting firm?" Thomas said: "We're still figuring this out too." Worst answer we've given.
- Tau: Sam asked "How do you scale 1-10? Are you still receiving payments after FDE?" Thomas delivered the BEST revenue breakdown yet: SaaS fee 5-10% + implementation fee (rate card, discount to Palantir) + maintenance/licensing fee ~50-60% of contract. Sam said it made sense.
Current answer (Tau version — USE THIS): "Three revenue components: a SaaS platform fee of 5-10%, an implementation fee priced on a rate card at a discount to Palantir, and ongoing maintenance/licensing at roughly 50-60% of the contract value. The implementation portion shrinks as a percentage with each new client because the core platform is reusable."
What made the Tau version work:
- Specific revenue components, not abstract framing
- Named percentages — investors can model this
- Palantir as rate card anchor — positions in a known category
- Maintenance/licensing as majority revenue — sounds like a software company, not consulting
- Natural answer to "are you still getting paid after FDE?" — yes, through maintenance/licensing
Action items:
- Standardize on the Tau version for every future call
- Never revert to "still figuring it out" or vague platform language
- Consider adding the ratio trajectory from Caesar's call: "First client is 70/30 custom/platform. By the fifth, it's 80% platform."
Status: RESOLVED — Tau call produced the answer. Must internalize and use consistently.
2. Positioning / Written Materials — "Wrapper on LLM" Fear
Came up in: Tau Ventures (2/6) — Sam Bogrov Frequency: 1/6 — but potentially affecting every call where materials are sent ahead
What happened: Sam said explicitly: "From the blurb it's like, so they're building a wrapper on an LLM." The written positioning triggers a fear that the verbal pitch does NOT trigger. Michael noted: "The way we pitch to customers is different than how we'd talk to VCs. You're probably seeing some of that."
Current problem: The deck/blurb is written for customers (clinical workflow framing) but investors read it differently. To a VC scanning quickly, AI + healthcare + copilot = "wrapper."
Suggested improvement:
- Rewrite the investor-facing blurb to lead with the BUSINESS, not the technology: "DaisyAI is the deployment partner health plans use to operationalize AI across clinical operations. We land with utilization management, prove ROI, and expand."
- Emphasize the services + software hybrid model upfront: implementation + ongoing platform
- Use the Palantir analogy in materials, not just verbally
- Separate the customer deck (clinical workflow) from the investor deck (business model + market)
- Have someone outside the team read the blurb cold and report what they think the company does
Status: URGENT — every investor who reads materials before a call may be forming "wrapper" impressions. Fix the blurb/deck immediately.
3. Demo Reliability for Product-Focused Investors
Came up in: Norwest VP (2/6) — Bayan Alizadeh Frequency: 1/6 — but the miss was significant
What happened: Couldn't get localhost working during the call. Bayan is product-focused (physics background) and explicitly said the demo is important for him. This was a BIG miss for a product-focused investor.
Context from other calls:
- Refract: Live demo crushed it — converted the conversation
- Sorensen: No demo needed — Chris is thesis-driven, drew parallels from his own portfolio
- Tau: No demo needed — Sam is business-model focused
- NextGen: No demo, and the conversation stayed abstract/skeptical as a result
The demo is a strategic asset — deploy based on investor type:
- Product-focused investors (Bayan, Caesar): need it early. It converts skepticism into conviction.
- Thesis-driven investors (Chris, Sam): may not need it at all. They're evaluating the business, not the product.
Suggested improvement:
- Have a deployed demo URL (not localhost) ready at all times
- Record a 3-5 minute walkthrough video as backup — send ahead to product-focused investors
- Before each call, assess: is this investor product-focused or thesis-focused? If product-focused, plan the demo into the call structure.
- For Norwest specifically: send the demo video ASAP as follow-up. This is recoverable.
Status: URGENT — need deployed demo URL or video before next product-focused investor call
4. Contract details / pricing / revenue structure
Came up in: Primary Ventures (1/30), Refract VC (2/5), Norwest VP (2/6) Frequency: 3/6 calls
What happened:
- Primary: Vague on pricing model ("not fully baked")
- Refract: "Small contract" and "haven't laid out exact terms"
- Norwest: Bayan asked about contract structure — decent but still TBD on specifics
- Tau: Not directly asked, but the revenue breakdown (SaaS + implementation + maintenance) provides the framework
- Sorensen: Not directly asked on pricing
- NextGen: Deborah assumed 6-7 figure contracts — we didn't confirm or frame
Current answer (use Tau framework): "Three revenue components: SaaS platform fee, implementation on a rate card, ongoing maintenance/licensing. First engagement is $X, expands as we prove value across their AI initiative roadmap."
Remaining gaps:
- Specific dollar ranges for each component (discovery, implementation, ongoing)
- How pricing scales with client size (regional plan vs. national payer)
- How the 12 AI initiatives translate to expansion revenue
Suggested improvement:
- Internalize ranges: Discovery sprint ($15-25K, 2-4 weeks), Implementation ($75-200K, 8-12 weeks), Ongoing ($20-30K/month)
- Frame: "We land with a scoping engagement at $X, build and deploy at $Y, then ongoing platform + support at $Z/month"
- Reference the 12 AI initiatives as expansion: "We land on one, prove value, expand across their stack"
- Confirm Deborah's 6-7 figure assumption next time it comes up
Source material: materials/deliverables/faq.md has pricing. Internalize for conversation.
Status: MOSTLY RESOLVED — Tau framework covers the model. Still need specific dollar ranges conversational-ready.
5. Vision / end state / deep vs. broad
Came up in: NextGen VP (2/5) Frequency: 1/6 — only Deborah pushed hard
What happened: Deborah said directly: "You need a pretty clear vision of the end state and a strong opinion on the direction the market is headed." She felt the pitch was still exploring, not asserting. Also pushed on deep vs. broad — Thomas gave "both" and she wanted a sequenced answer.
Current answer: Real-time payer-provider integration, eliminate duplicative work. Broad vision but no sequence.
Suggested improvement:
- Sequence it: "Next 12 months: go deep with 3-5 payers on UM — prove the model, build the platform. 12-24 months: expand within those payers across their other AI initiatives (care management, prior auth, retrospective review). 24+ months: the platform is the payer operating system for AI-enabled clinical operations."
- Frame as hypotheses (Deborah's advice): "We're testing three hypotheses: (1) payers will pay for embedded AI engineering talent, (2) the core analytical layer is reusable across payers, (3) landing on UM opens the door to adjacent workflows."
- Have a strong opinion: "We believe every health plan will need an AI layer for clinical operations within 3 years. No one is building it with the right combination of healthcare depth and technical execution. We are."
Note: Only 1/6 investors pushed this. The other 5 accepted the stage. This may be Deborah-specific rather than universal, but the answer improvement is still valuable.
Status: Needs strategic refinement — MEDIUM PRIORITY (downgraded from high — not recurring)
6. Differentiation / moat (when challenged)
Came up in: NextGen VP (2/5) — Deborah opened with skepticism Frequency: 1/6 — not recurring across other investors
What happened: Deborah framed the entire conversation around differentiation being hard. Thomas actually raised the moat problem himself ("what's the defensibility if these products are so cross-applicable? It can't be that hard.") — honest but self-defeating.
Current answer: Durable relationships + incentive understanding + teaching flywheel (conceptual)
Suggested improvement:
- Don't raise the problem without immediately delivering the answer. Acknowledge briefly, pivot fast.
- Three layers of moat: (1) Healthcare depth — we understand incentives, not just workflows. (2) Compounding data — every review makes the system smarter for that payer's specific patterns. (3) Switching cost — once we're integrated into their EMR/data systems and their team is trained, ripping us out is harder than keeping us.
- The Palantir analogy works: Palantir's moat isn't their software — it's that they're embedded. Same principle, healthcare-native.
- Counter the "models are the same" argument: "Models are commodity. Knowing WHERE to apply them in healthcare — which workflow, which decision point, which data source, how to handle liability — that's the hard part. We have 12 months of that knowledge compounding."
Status: Needs crisp delivery — LOW PRIORITY (only 1/6 asked, but keep answer ready)
7. Market size / TAM
Came up in: Refract VC (2/5) — Caesar flagged it Frequency: 1/6 — surprisingly low
What happened: Caesar: "We have to wrap our heads around the market size and the opportunity." No direct number asked, but it's an open question for them.
Current answer: "Healthcare back-office is massive. UM alone is multi-billion." (from objections.md — no specific numbers)
Suggested improvement:
- Specific: X nurses doing UM nationally, $Y spend on UM outsourcing, $Z total payer admin costs
- Bottom-up: X health plans x $Y average contract x expansion = $Z addressable in 3 years
- Reference Charter Health (Refract portfolio) landing 7-figure Blue Cross Michigan as market proof
- Frame: "UM is the wedge ($XB). Healthcare admin back-office is $X00B. AI restructures all of it."
Status: Needs research + modeling — MEDIUM PRIORITY
Anticipated Gaps (haven't come up directly)
8. Unit economics at scale
Likely from: Any investor pushing past scalability framing Current answer: None Suggested: Model single engagement P&L. Show margin trajectory as platform matures. The Tau revenue breakdown (SaaS + implementation + maintenance) gives a natural P&L structure. Status: Needs financial modeling
9. Data strategy / compounding advantage
Likely from: Technical or healthcare-informed investors Current answer: TBD in FAQ. Mentioned ADT/HL7 in Refract call. Norwest call showed strong HL7/ADT/ORU technical specifics. Suggested: Access → accumulate → compound narrative. Norwest-level technical specifics show credibility. Status: Needs technical articulation
10. Competitive landscape specifics — NOW BATTLE-TESTED
Came up in: Refract VC (2/5 — market size framing), Seae Ventures (2/17 — direct competition question) Frequency: 2/7 — and Seae flagged it as THE diligence gate for their full team Current answer: Thomas's Seae answer was strong: "We've never thought about prior auth companies as competitors — payer already automated 100% of PA. Real comps are consulting orgs, Palantir. Cohere/Cahir been trying to get into concurrent for 2 years." But needs formalization into a one-pager. **Intel growing from investor conversations:
- Fourier Health (NextGen portfolio) — AI medical record summarization, health systems
- Lumara Health (NextGen intel) — AI agent orchestration, benefits nav + triage
- Logical Health (NextGen intel) — payer member engagement
- Charter Health (Refract portfolio) — selling to insurers, Blue Cross Michigan
- Valerie Health (Primary portfolio) — AI-enabled managed service, specialty practices
- J2 Health (Primary portfolio) — network adequacy for regional plans
- Alafia (Tau portfolio) — fraud/miscoding for payers
- SNF AI platform (Sorensen portfolio) — reimbursement optimization for skilled nursing
- Palantir, MCG/InterQual (market) Suggested: Need a formal one-pager with: (1) Prior auth companies NOT competitors (payers already automated PA), (2) Consulting orgs are real comps but lack AI-native talent, (3) Palantir is expensive and not healthcare-deep, (4) Cohere/Cahir trying concurrent for 2 years with no traction — FDE is the moat, (5) Market map showing where each player sits. Status: UPGRADED TO HIGH PRIORITY — Seae confirmed competition is their #1 diligence question. Need one-pager before full team pitch.
Feedback Loop
When an answer gap is addressed:
- Update the answer here with the new version + date
- Update
materials/narrative/objections.mdif it's a core objection - Update
materials/deliverables/faq.mdif it's a common question - Mark status as "Ready" with date
Recently Resolved
- Scalability / revenue model — resolved by Tau call (2/6). SaaS + implementation + maintenance framework. Standardize.
- Contract pricing framework — mostly resolved by Tau framework. Need specific dollar ranges.
New Validation (Wavemaker 2/19)
- Services vs. SaaS framing: Michelle Wang explicitly validated services-first revenue: "I'd rather have an honest presentation... services can be more sticky than fake ARR." First investor to say this outright. Validates the thesis that we should NOT hide the services component. Actually lead with it for investors who share this worldview.
- No new gaps surfaced. Wavemaker call was more of a validation conversation than a challenging one. Michelle's questions were probing but fair, and answers were adequate-to-strong across the board. The only area for improvement: roadmap answer could have articulated the productization sequence more clearly (3-6 months deep → identify replicable components → productize → sell to others).