Portfolio Manager
Screening for Undervalued AI Stocks — 5 Companies the Market Is Sleeping On
Key Takeaway
Our stock screener agent found 5 AI companies trading below P/E 30 with 25%+ revenue growth and positive free cash flow — the kind of names that don't show up in hype-driven coverage.
The Problem
AI stock coverage is broken. Every financial media outlet covers the same 10 names. NVDA. MSFT. GOOGL. META. The magnificent seven, plus whatever just IPO'd.
Meanwhile, there are companies doing $500M+ revenue with 30% growth, positive cash flow, real AI products in production — trading at reasonable multiples because they don't have a cult following on Twitter/X.
I don't want hype stocks. I want compounders. Companies where the fundamentals are growing faster than the stock price. Where the AI narrative is backed by actual revenue, not a chatbot demo.
Screening for these manually is a research project. You're reading 10-Ks, checking quarterly filings, comparing growth rates, looking at technical charts. Per company, that's 30-45 minutes of work. If you're screening from a universe of 200+ AI-adjacent names, that's a week of full-time work.
The Solution
Hari runs a monthly US stock screener that filters the universe through both fundamental and technical criteria. The fundamental filter catches quality — real growth, real cash flow, reasonable valuation. The technical filter catches timing — not overbought, trend intact.
What survives both filters gets a deep-dive analysis: competitive moat, management quality, catalyst calendar, and risk factors. The output isn't "buy these" — it's "research these." The human still makes the decision.
The Process
Screening criteria:
yamlShow code
# ai-stock-screener config
schedule: "0 8 1 * *" # 1st of each month, 8AM UTC
universe: "US equities, market cap > $1B, AI revenue exposure > 50%"
fundamental_filters:
pe_ratio: { max: 30 }
revenue_growth_yoy: { min: 25 } # percent
free_cash_flow: { min: 0 } # must be positive
ai_revenue_pct: { min: 50 } # >50% revenue from AI products
technical_filters:
rsi_14: { max: 70 } # not overbought
price_vs_sma200: "above" # trend intact
volume_trend: "stable_or_rising" # not dying on the vine
deep_dive_fields:
- competitive_moat
- management_quality
- catalyst_calendar
- bear_case
- fair_value_estimate
The screening pipeline:
pythonShow code
def run_screen(universe, filters):
# Phase 1: Quantitative filter
candidates = []
for stock in universe:
fundamentals = fetch_fundamentals(stock.ticker) # Alpha Vantage
technicals = fetch_technicals(stock.ticker)
if (fundamentals.pe_ratio < filters.pe_max
and fundamentals.revenue_growth > filters.rev_growth_min
and fundamentals.fcf > 0
and technicals.rsi_14 < filters.rsi_max
and technicals.price > technicals.sma_200):
candidates.append(stock)
# Phase 2: AI exposure validation (web research)
ai_validated = []
for stock in candidates:
exposure = research_ai_exposure(stock) # analyst reports, 10-K search
if exposure.ai_revenue_pct >= filters.ai_pct_min:
ai_validated.append((stock, exposure))
# Phase 3: Deep dive (top 5 by composite score)
ranked = rank_by_composite(ai_validated) # growth + value + momentum
return [deep_dive(stock) for stock in ranked[:5]]
Sample output from the March 2026 screen:
View details
📊 AI STOCK SCREEN — March 2026
5 names passed all filters from 214 screened
#1 — [COMPANY A] — Enterprise AI Infrastructure
P/E: 24.3 | Rev Growth: 42% YoY | FCF: $180M
AI Exposure: 78% (inference optimization platform)
Moat: Switching costs + proprietary model compression IP
RSI: 54 | +12% above 200-SMA
Catalyst: Q1 earnings (April 22), new GPU partnership rumored
Risk: Customer concentration (top 3 = 45% revenue)
Fair Value: $78-92 (current: $64)
#2 — [COMPANY B] — AI-Powered Cybersecurity
P/E: 19.8 | Rev Growth: 31% YoY | FCF: $95M
...
The Results
214 AI-adjacent companies
Universe screened
23
Passed fundamental filter
14
Passed technical filter
8
Passed AI exposure validation
5
Final deep-dive list
12 minutes
Screening time (agent)
~40 hours
Equivalent manual research time
3 of 5 outperformed sector avg
Hit rate (prior screens, 6-month forward)
Try It Yourself
The screening skill uses Alpha Vantage for fundamentals and technicals, plus web research for AI exposure validation. You need the alpha-vantage skill and web search configured on Mr.Chief.
Adjust the filters to your style. If you're more aggressive, raise the P/E cap and lower the RSI threshold. If you're conservative, add a debt-to-equity filter. The framework is the value — the parameters are yours.
The market's obsession with 10 stocks means it's ignoring 200 others. That's not a problem. That's an edge.
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