Palantir Is Now Too Cheap to Ignore - What Changed?
palantir looks “too cheap to ignore” after Morningstar says the stock trades 24% below its fair value estimate, following a market rotation out of early AI winners. The pitch centers on continued triple-digit growth, strong customer retention, and an AI decision-making platform narrative—plus a new NVIDIA Nemotron partnership for secure, sovereign deployments.
Key Takeaways
- Morningstar says palantir trades 24% below its fair value estimate of $153.
- The report emphasizes continued triple-digit growth and best-in-class customer retention.
- Competition risk is real as AI labs attempt to copy Palantir’s deployment strategy.
- NVIDIA Nemotron + Palantir’s sovereign stack targets air-gapped AI deployments while preserving data and model ownership.
Why is palantir suddenly “too cheap to ignore”?
Morningstar frames a key shift: Palantir is no longer trading like a perpetual high-flier. In its view, the stock is trading 24% below Morningstar’s fair value estimate, a stark contrast to how shares typically changed hands at a premium in prior years.
The timing, Morningstar argues, is tied to “market rotation” away from many early AI highflyers—pulling Palantir down by more than 40% from its 2025 high. Despite that pressure, Morningstar says it sees opportunity in the pullback, citing the continuation of triple-digit growth and what it calls best-in-class customer retention.
What does Morningstar think supports the valuation?
Morningstar’s thesis is built around a long runway for AI decision-making software. It points to a fair value estimate of $153 and notes the valuation implies a 2026 enterprise value/sales multiple of 48 times. It also says it believes the market is still in the “early innings of an AI revolution.”
In that framework, Morningstar forecasts a total addressable market growing to $1.4 trillion by 2033. It projects five-year average annual revenue growth of 45% and expects gross margin to remain in the 83%-85% range over the next 10 years, balancing higher-margin enterprise onboarding with potential cloud cost pressures.
Morningstar also highlights an industry dynamic that can cut both ways: declining costs of AI inference and improvements in agentic large language models may lower barriers to entry in Palantir’s segment, increasing competitive churn.
How does the NVIDIA Nemotron partnership fit the bigger picture?
NVIDIA’s announcement adds a concrete “secure deployment” angle to Palantir’s AI narrative. NVIDIA says Palantir’s new intelligent engine uses NVIDIA Nemotron open models to serve U.S. government agencies, with domain-optimized harnesses designed to help customers retain control over proprietary data, model weights, and deployment environments. NVIDIA also stresses that the approach brings Nemotron open models into air-gapped environments that are completely isolated from unsecured networks.
NVIDIA further says agencies can run customized Nemotron models on their own infrastructure, train on their own data, and retain full ownership of the resulting models—including the weights that encode operational knowledge. The post links this capability to Palantir’s “Sovereign AI Operating System” (built on AIP, Foundry, Ontology, and Apollo), which NVIDIA describes as providing operational and data authorization layers with architecturally enforced isolation and full auditability. (External reading: NVIDIA blog.)
Seeking Alpha, meanwhile, characterizes the Palantir-Nvidia collaboration as potentially huge for palantir. One Seeking Alpha piece argues the integration positions Palantir as a primary beneficiary of federal AI spending and includes a bull-case scenario in which government revenue could triple, projecting a $6-$7B annual run rate from federal contracts within two years.
What risks could still make palantir “cheap”?
Morningstar’s caution is straightforward: AI labs attempting to copy Palantir’s deployment strategy could raise competition, and Morningstar says it has “baked that risk” into its fair value estimate. It also warns that Palantir’s high valuation multiple leaves “no margin for error” if investors lose confidence in the durability of growth.
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