Research Portal

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

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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.

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Clear
Silicon Stack Data Center Fabric AI Software Power + Grid Robotics
MSFT Cloud, Data & AI Software

Microsoft

Enterprise AI platform

Detail page

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

Price $530.61
1D change -0.99%
Market cap $3.94T
Sector Technology
ORCL Cloud, Data & AI Software

Oracle

AI cloud infrastructure and databases

Detail page

Oracle Cloud Infrastructure is increasingly used for large AI training and inference clusters.

Price $116.10
1D change +0.82%
Market cap $361.97B
Sector Technology
CRWV Cloud, Data & AI Software

CoreWeave

GPU cloud infrastructure

Detail page

CoreWeave is a pure-play AI cloud focused on GPU capacity for training and inference workloads.

Price $46.40
1D change +6.28%
Market cap $25.59B
Sector Technology
SNOW Cloud, Data & AI Software

Snowflake

Enterprise data cloud for AI

Detail page

AI applications depend on governed, usable enterprise data, which is Snowflake's core layer.

Price $275.88
1D change +2.35%
Market cap $97.33B
Sector Technology

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.

On smaller screens, swipe this table horizontally to compare the full set.

Metric MSFT ORCL CRWV SNOW
Price $530.61 $116.10 $46.40 $275.88
1D Change -0.99% +0.82% +6.28% +2.35%
Market Cap $3.94T $361.97B $25.59B $97.33B
Enterprise Value $4.01T $488.50B $71.67B $97.64B
Trailing P/E 27.7 18.2 -12.6 -86.8
Forward P/E 21.9 10.5 -22.6 91.1
PEG Ratio 1.57x 0.63x — 4.94x
Price / Sales 11.4 5.0 3.4 17.9
EV / Revenue 11.6 6.8 9.4 18.0
Revenue Growth 18.8% 29.6% 112.5% 35.1%
Earnings Growth 32.3% 54.5% — —
Gross Margin 67.7% 64.0% 67.4% 67.0%
Operating Margin 49.8% 35.6% -1.9% -17.0%
Net Margin 41.2% 26.4% -25.4% -20.1%
ROE 34.2% 41.2% -43.6% -48.1%
Free Cash Flow $2.99B $-45.85B $-9.09B $1.74B
FCF Margin 0.9% -63.9% -119.7% 32.0%
Debt / Equity 0.28x 2.52x 10.27x 1.29x
Current Ratio 1.23x 1.17x 0.46x 0.94x
Dividend Yield 0.69% 1.72% 0.00% 0.00%
Next Earnings Jan 27, 2027 Dec 14, 2026 Nov 10, 2026 Dec 02, 2026
Quarterly Revenue $92.28B $19.34B $2.58B $1.55B
Revenue QoQ +2.5% +0.8% +23.9% +11.2%
Quarterly Net Income $36.63B $4.76B $-626.0M $-191.7M
Net Income QoQ +2.4% +10.6% +15.4% +35.1%

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.

ORCL thesis lens

AI cloud infrastructure and databases

Why it could benefit

  • Oracle Cloud Infrastructure is increasingly used for large AI training and inference clusters.
  • Database and enterprise application customers create a natural path for AI agents and automation.
  • Sovereign and regulated workloads can prefer Oracle's enterprise footprint.

Moat / edge

  • Deep enterprise database installed base.
  • Growing cloud infrastructure backlog.
  • Strong relationships with regulated industries and governments.

What to watch

  • OCI revenue growth and remaining performance obligations.
  • Capex intensity versus cloud gross margin.
  • AI infrastructure customer concentration.

Key risks

  • Cloud buildout requires heavy capital spending.
  • Competition from AWS, Azure, and Google Cloud remains intense.

CRWV thesis lens

GPU cloud infrastructure

Why it could benefit

  • CoreWeave is a pure-play AI cloud focused on GPU capacity for training and inference workloads.
  • It gives the dashboard direct exposure to neocloud demand outside the hyperscalers.
  • Fast customer growth can signal whether specialized GPU clouds keep taking share.

Moat / edge

  • Purpose-built GPU infrastructure and fast deployment model.
  • Deep relationships with AI labs and enterprise AI buyers.
  • Focused operating model compared with general-purpose clouds.

What to watch

  • Customer concentration and contract duration.
  • Debt, capex, and GPU utilization.
  • Competitive response from hyperscalers.

Key risks

  • High capital intensity can amplify execution risk.
  • Demand visibility may change quickly if AI training economics shift.

SNOW thesis lens

Enterprise data cloud for AI

Why it could benefit

  • AI applications depend on governed, usable enterprise data, which is Snowflake's core layer.
  • Cortex and related AI services can help customers build AI directly against their data.
  • Consumption growth can improve as AI workloads expand data usage.

Moat / edge

  • Large enterprise data footprint.
  • Cross-cloud data platform with strong ecosystem integrations.
  • Consumption model can scale with workload growth.

What to watch

  • Product revenue growth and net retention.
  • Cortex AI adoption.
  • Competition from Databricks, hyperscalers, and lakehouse tools.

Key risks

  • Optimization by customers can pressure consumption.
  • AI monetization may take longer than platform enthusiasm implies.