# Strict Latent AI Alpha Screen — Methodology

Generated: 2026-05-06 America/Los_Angeles context. This is a research-prioritization screen, not investment advice.

## User clarification implemented

The earlier screen was too broad. This revision excludes companies that are already clearly used in the AI supply-chain build-out: AI chips, wafer-fab tools/materials, semiconductor processing, advanced packaging, CPO/optical interconnect, data-center power, cooling, transformers, racks, fire/safety services explicitly sold into data centers, and obvious data-center construction beneficiaries.

## What “not used yet” means in this dashboard

Absence is difficult to prove. I therefore use a stricter but honest label: **no clear current AI/data-center/fab/advanced-packaging/CPO/optics/power participation was found in the spot checks used for this screen.** Each candidate still requires follow-up review of its latest annual report, investor presentation, backlog, customer concentration, and transcript language before capital is deployed.

## Alpha Score

Alpha Score = Latent Fit + Discovery Gap + Valuation Setup + Catalyst Density + Execution/Quality - Hype Penalty.

- Latent Fit: how naturally the company's capability could map to AI infrastructure if demand spills beyond obvious suppliers.
- Discovery Gap: how under-followed or non-consensus the AI pathway appears.
- Valuation Setup: for US names, a rough score based partly on the finance-tool market-cap and P/E snapshot on 2026-05-06 UTC; for non-US names, a qualitative setup because reliable non-US finance snapshots did not return in-session.
- Catalyst Density: plausible events that could make the latent pathway visible.
- Execution/Quality: business quality and ability to scale.
- Hype Penalty: penalty for category adjacency that may already be crowded or too close to current AI supply.

## Output files

- assets/data/companies_strict_latent.csv — ranked 50 US + 50 non-US candidates
- assets/data/excluded_direct_ai_supply_chain.csv — names removed for direct current AI-chain exposure
- assets/data/source_pack.csv — research source links
- assets/images/*.png — visualization pack

## Important limits

This dashboard is not a formal valuation model. It does not claim any company has zero AI-related revenue. It identifies stocks where the public AI thesis appears not yet obvious from the sources reviewed and where the company owns capabilities that could become relevant if supply constraints spread into second-order parts, materials, water, filtration, motion, security, safety, recycling, and MRO layers.