524 applications ingested · Scored against 6-criteria rubric · Tier classification complete · Reviewer assignments ready · 2.1 hours total processing
| Criterion | Cohort Avg | AI Finding — Sample: Verdant Climate Tech | Evidence |
|---|---|---|---|
Problem Clarity Is the problem well-defined and evidence-backed? |
Strong 84 | Verdant identifies industrial water overuse in textile manufacturing with cited data: 1.5T liters/year wasted in South Asian supply chains. Problem statement consistent across executive summary and founder narrative sections. Market framing specific and validated. |
Exec Summary · p.2Founder Bio |
Solution Differentiation Why this solution, why now, why this team? |
Strong 79 | Real-time IoT sensor network for dye-bath water recycling. Cites 3 issued patents and pilot at Tier 1 supplier for H&M. Competitive moat well-articulated. No reference to alternatives in narrative — competitive landscape section missing. Competitive analysis required before panel review. Strong core, incomplete framing. |
Solution · p.4Traction · p.7 |
Traction & Validation What evidence exists that this works? |
Moderate 62 | Pilot data shows 38% water reduction at one facility. Revenue: $240K ARR. However, pilot sample size = 1 facility, 6 months — insufficient to generalize. LOI from second customer cited but not dated or signed. Traction claim requires pilot expansion data or signed LOI before cohort acceptance. |
Traction · p.6Appendix B |
Team Capability Does the team have the expertise to execute? |
Strong 81 | Founding team: ex-Xylem water engineer (12 yrs) + supply chain SaaS operator (2 exits). Advisor network includes textile industry veterans. 4 of 6 full-time hires have domain experience. No gap in execution capacity identified. |
Team · p.9Advisor Bios |
Market Opportunity Is the addressable market credible and large enough? |
Moderate 58 | TAM cited as $4.2B industrial water management from a 2021 McKinsey report — outdated source, not segmented to SAM/SOM. No bottoms-up market build. Cohort average for market section is notably lower than prior cycles — pattern across 64 applications this cycle. Market section is the single largest scoring gap across the cohort. May warrant rubric calibration for future cycles. |
Market · p.5 |
Impact Thesis What change does this create, for whom, how measured? |
Moderate 67 | Impact thesis: water saved per facility and supply chain GHG reduction. Measurable outputs stated. No baseline or counterfactual defined. SDG 6 and SDG 13 cited without theory of change narrative. Sponsor reporting will require stronger causal framing. |
Impact · p.8 |