Palantir Technologies Inc.
A data analytics and AI platform company providing software solutions for large-scale data integration, analysis, and decision-making to government and commercial clients.
What the page says before deeper research
Quality, growth, value, ownership, risk, and source confidence.
Moat 9.2/100 with low retention risk and high switching costs.
Growth appears healthy from +68% YoY revenue growth.
Forward P/E of 96.5x versus +68% growth gives a 1.4x multiple-to-growth read.
No SEC-backed 13F layer is matched yet, so ownership confirmation is unavailable.
Retention and AI disruption risks are low; valuation is not flagged expensive.
Fundamentals from finnhub as of 2026-05-17; ownership confirmation is not available here.
Revenue growth shows whether PLTR’s platform is still expanding fast enough to support a premium valuation.
Beginner valuation check
Data pending from FMP or Finnhub.
Positive price performance shows recent market sentiment, not a full investment thesis.
Forward P/E around 96.5x means investors pay about $96.5 for each expected $1 of future profit per share, usually the next 12 months or next fiscal year. It is a forecast, not a fact.
A P/E around 140.8x means investors pay about $140.8 for each $1 the company earned per share over the last 12 months, usually the last four quarterly reports.
Source: market data index. As of May 21, 2026. P/E can be unavailable or misleading when earnings are negative.
Beginner guide
Palantir builds software that helps governments and big companies make sense of huge amounts of data, like solving a giant jigsaw puzzle with a computer.
A data analytics and AI platform company providing software solutions for large-scale data integration, analysis, and decision-making to government and commercial clients.
Palantir Technologies Inc. makes money through Government (~55% of revenue) and Commercial (~45% of revenue).
Deep client data integration creates 'digital gravity' - customers can't easily extract years of enriched, linked data
Palantir Technologies Inc. can disappoint if execution, competition, valuation, or demand cycles weaken growth, margins, customer retention, or investor confidence.
Palantir Technologies Inc. is like a specialized business engine: investors want to know whether government can keep producing durable cash flow.
You are basically betting that Palantir Technologies Inc. can keep turning government into durable value while managing execution, competition, valuation, or demand cycles.
A 0-100 shortcut for how defensible the business looks in this company brief. Palantir Technologies Inc. is scored at 9.2.
How painful it is for customers to leave. this company brief rates Palantir Technologies Inc. as high.
Whether existing customers tend to spend more or less over time. The company brief model uses 114%.
The main pieces of the company here are Government and Commercial.
Price divided by earnings. It is a quick valuation check, but it can mislead when earnings are temporarily high, low, or negative.
A quarterly filing that shows what many large institutional investors owned at quarter end.
The first four questions
Palantir’s government business can support the story if deep client data integration keeps creating switching friction and customer expansion holds up.
PLTR can get hit if execution, competition, valuation, or demand cycles weaken growth, customer retention, or investor confidence.
Government
Next earnings date unavailable from configured sources.
Bull / Neutral / Bear
Investors continue paying up for a software platform with high switching costs, but the multiple matters because the stock already reflects strong growth expectations.
Forward P/E around 96.5x stays tied to durable growth and customer expansion.
Government remains the core engine while Palantir keeps monetizing embedded data workflows and AI use cases across clients.
Government stays strong and revenue growth remains near the current ~68% pace or improves.
Investors continue paying up for a software platform with high switching costs, but the multiple matters because the stock already reflects strong growth expectations.
Forward P/E around 96.5x stays tied to durable growth and customer expansion.
If growth decelerates or customers start questioning the platform’s value, the premium multiple can compress quickly even if the business remains large.
Revenue growth cools, retention weakens, or ownership flow stays absent.
Beginner checklist
Needs earnings calendar data from a provider.
Revenue growth shows whether PLTR’s platform is still expanding fast enough to support a premium valuation.
Margin trend needs company financial statement data; do not infer it from price movement.
Forward P/E is a quick valuation anchor, but it must be compared with growth and business quality.
No SEC-backed ownership rows are available for this ticker yet.
Needs insider transaction data from a provider.
For PLTR, the key business-line check is whether government remains the strongest engine of durable demand.
Palantir Technologies Inc. is exposure to software operating model with high switching costs and 114% net revenue retention.
Deep client data integration creates 'digital gravity' - customers can't easily extract years of enriched, linked data
The main question is whether the company can keep customer value compounding without margin pressure eroding the moat.
Pro access unlocks the workflow simulator for this company brief.
Simulator coverage pending
This ticker has a company brief, but richer workflow modules have not been built yet.
No SEC-backed 13F rows are matched for this ticker yet. We do not fabricate ownership rows.
- Deep client data integration creates 'digital gravity' - customers can't easily extract years of enriched, linked data
- Government contracts with multi-year commitments and security clearance requirements create regulatory switching barriers
- Forward Deployed Engineers become embedded in client operations, creating human switching costs beyond technology
- Custom ontologies and data models represent institutional knowledge that would take competitors years to replicate
- Network effects strengthen as more data sources feed into unified analytical platforms, improving insights quality
- AI advantage grows over time through proprietary training on client-specific datasets and use cases