Research Portal

U.S.-listed market research with live data and structured thesis notes.

Side-by-side research view

Compare names across metrics and research quality

Use up to 4 U.S.-listed names from this dashboard to compare valuation, growth, cash flow, balance-sheet strength, and the curated investment case in one place.

4 stocks in current compare
4 max names side by side
24 shared metrics lined up

Build a compare set

Enter comma-separated tickers from the dashboard universe. Duplicate tickers are ignored automatically.

Clear
Compute Stack AI Platforms Power Buildout Robotics
MSFT Platforms & Software

Microsoft

Enterprise AI platform

Detail page

Azure is one of the main cloud platforms funding and serving AI workloads.

Price $381.87
1D change -1.84%
Market cap $2.84T
Sector Technology
GOOGL Platforms & Software

Alphabet

Consumer + cloud AI platform

Detail page

Alphabet can monetize AI across Search, YouTube, Cloud, Workspace, and Android.

Price $301.00
1D change -2.00%
Market cap $3.64T
Sector Communication Services
AMZN Platforms & Software

Amazon

Cloud + AI infrastructure platform

Detail page

AWS sells the compute, storage, networking, and managed services behind enterprise AI adoption.

Price $205.37
1D change -1.62%
Market cap $2.20T
Sector Consumer Cyclical
META Platforms & Software

Meta Platforms

AI-enabled ad platform

Detail page

AI can improve recommendation quality, ad targeting, and monetization across Meta's family of apps.

Price $593.66
1D change -2.15%
Market cap $1.50T
Sector Communication Services

Shared metric table

Live market metrics plus reported quarterly revenue and profit QoQ rows.

Green and red only apply where direction is meaningful. Quarterly revenue and profit cells inherit the sign of the reported QoQ change, which can swing sharply when the prior quarter included a one-time item.

Metric MSFT GOOGL AMZN META
Price $381.87 $301.00 $205.37 $593.66
1D Change -1.84% -2.00% -1.62% -2.15%
Market Cap $2.84T $3.64T $2.20T $1.50T
Enterprise Value $2.87T $3.58T $2.26T $1.51T
Trailing P/E 23.9 27.8 28.6 25.3
Forward P/E 20.3 22.4 22.0 16.5
Price / Sales 9.3 9.0 3.1 7.5
EV / Revenue 9.4 8.9 3.2 7.5
Revenue Growth 16.7% 18.0% 13.6% 23.8%
Earnings Growth 59.8% 31.1% 5.0% 10.7%
Gross Margin 68.6% 59.7% 50.3% 82.0%
Operating Margin 47.1% 31.6% 10.5% 41.3%
Net Margin 39.0% 32.8% 10.8% 30.1%
ROE 34.4% 35.7% 22.3% 30.2%
Free Cash Flow $53.64B $38.09B $23.79B $23.43B
FCF Margin 17.6% 9.5% 3.3% 11.7%
Debt / Equity 0.32x 0.16x 0.43x 0.39x
Current Ratio 1.39x 2.00x 1.05x 2.60x
Dividend Yield 95.00% 28.00% — 35.00%
Next Earnings Apr 29, 2026 Apr 23, 2026 Apr 30, 2026 Apr 29, 2026
Quarterly Revenue $81.27B $113.83B $213.39B $59.89B
Revenue QoQ +4.6% +11.2% +18.4% +16.9%
Quarterly Net Income $38.46B $34.45B $21.19B $22.77B
Net Income QoQ +38.6% -1.5% +0.0% +740.5%

MSFT thesis lens

Enterprise AI platform

Why it could benefit

  • Azure is one of the main cloud platforms funding and serving AI workloads.
  • Copilot can raise average revenue per user across Microsoft 365, GitHub, Dynamics, and security products.
  • Its distribution into nearly every large enterprise makes AI attach rates especially valuable.

Moat / edge

  • Massive installed base in productivity and enterprise infrastructure.
  • Deep cloud stack plus model partnerships and proprietary tooling.
  • Switching costs are high once AI workflows are embedded in daily software.

What to watch

  • Azure growth excluding currency and one-time items.
  • Copilot user adoption, pricing durability, and seat expansion.
  • Capex efficiency versus AI revenue realized.

Key risks

  • Capex could stay ahead of monetization for longer than the market expects.
  • Competition from Google, Amazon, and specialized AI software vendors.

GOOGL thesis lens

Consumer + cloud AI platform

Why it could benefit

  • Alphabet can monetize AI across Search, YouTube, Cloud, Workspace, and Android.
  • Gemini gives it a vertically integrated way to improve both user engagement and developer tooling.
  • Google Cloud adds direct exposure to enterprise model training and inference demand.

Moat / edge

  • Search and YouTube create unmatched data, traffic, and distribution.
  • Custom infrastructure and TPU capabilities support scale economics.
  • A full consumer-to-enterprise stack improves AI product iteration speed.

What to watch

  • Search monetization under AI Overviews and agentic search.
  • Google Cloud operating leverage and backlog conversion.
  • Gemini usage and developer adoption.

Key risks

  • Search economics may shift if query patterns change materially.
  • Regulatory pressure could limit bundling or data advantages.

AMZN thesis lens

Cloud + AI infrastructure platform

Why it could benefit

  • AWS sells the compute, storage, networking, and managed services behind enterprise AI adoption.
  • Anthropic exposure adds indirect upside to one of the leading frontier-model companies.
  • Retail and logistics can also benefit from AI productivity gains internally.

Moat / edge

  • Leading cloud footprint and long enterprise relationships.
  • Broad service catalog makes AWS sticky once workloads scale.
  • Cash generation from commerce funds infrastructure expansion.

What to watch

  • AWS growth relative to peers and capex intensity.
  • AI services mix, especially higher-margin managed offerings.
  • How much of Anthropic value the market begins to recognize.

Key risks

  • Commodity compute pricing can pressure returns on investment.
  • Retail margin or logistics issues can muddy the AI thesis.

META thesis lens

AI-enabled ad platform

Why it could benefit

  • AI can improve recommendation quality, ad targeting, and monetization across Meta's family of apps.
  • Meta can also monetize AI assistants and creator tools over time.
  • Its open-weight ecosystem may help it shape the developer stack even beyond direct product revenue.

Moat / edge

  • Enormous audience scale and ad inventory.
  • Rich engagement data and feedback loops for recommendation systems.
  • High operating leverage when better models improve ad yield.

What to watch

  • Ad load and pricing trends tied to AI recommendation gains.
  • Reality Labs losses versus core-platform cash generation.
  • Usage and monetization of Meta AI tools.

Key risks

  • Heavy spending can compress margins if revenue lags.
  • Privacy or regulatory changes can pressure targeting efficiency.