AI Platform
Due diligence that closes deals.
A full product build for Aventro - AI-verified investor-readiness scoring across team, IP, traction, financials, and integrity. Evidence rooms, what-if simulations, real-time collaboration. Brand, design, product, build - end-to-end.
- Status
- Live in production
- Audiences
- Founders + investors
- Verification
- AI-assisted
The problem
Diligence cycles kill more deals than weak ones do.
Founders chase trust signals. Investors chase verification. Both sides end up with the same problem - there's no shared, neutral surface for proving what's actually true about a company. By the time enough has been verified to close, momentum has already bled out, and good deals die in the gap between conviction and confirmation.
The mark
Aventro
Designed end-to-end
The approach
Move verification before the meeting, not after.
Aventro flips the order. Founders upload primary evidence - financials, IP filings, traction, integrity signals - and the platform runs AI-assisted verification against trusted sources. The output is a readiness score across five weighted categories, plus an evidence room investors can step into to validate any single claim. What-if simulations let teams test scenarios without committing to numbers.
Brand system
Built on a calm, branded surface
Move verification before the meeting, not after.
Process
How it came together
- 01
Brand discovery
Mapped the trust → conviction story arc that anchors the entire product narrative.
- 02
Product architecture
Defined the readiness model - five categories, weighted scoring, evidence handoff loop.
- 03
Design + build
Visual system, UI, frontend, backend, and AI verification integrations - end-to-end.
- 04
Launch
Shipped to production at aventro.ai. Live and in use by founders today.
Operating principle
Move verification before the meeting, not after
LinksToBook · brand line
The result
A trust layer that closes deals instead of killing them.
Live at aventro.ai. Founders use it to walk into investor meetings already verified; investors use it to short-circuit the back-and-forth and focus on the deal. The product looks like the conviction it's selling - calm, rigorous, AI-native without being noisy about it.
What we delivered
Four main things, end-to-end.
Brand & visual system
Name expression, voice, type system, color, and the trust-coded surface that anchors the entire product.
Product strategy & UX
Information architecture, the readiness scoring model, evidence loops, and the founder ↔ investor handoff.
Frontend product
Full app build - interactions, motion, multiplayer collaboration, and the scoring + evidence surfaces.
Backend & AI
Verification engine, source matching, document intake, simulator runtime, and the evaluation pipeline.
What's inside
Product capabilities.
Readiness scoring
Five weighted categories - team, IP, traction, financials, integrity.
Evidence rooms
Investors validate any claim at the source - single click, single surface.
What-if simulator
Test scenarios without committing to numbers; rerun the score with one toggle.
Real-time collab
Multiplayer reviews, comments, and shared decision flow across founders and investors.
Surface tour
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