Analysts Stay Bullish as Palantir Slides 3%

Palantir Technologies shares fell about 3% during Tuesday trading despite fresh analyst support for the company’s enterprise AI business. Wolfe Research upgraded the stock to Hold and set a $207 price target; UBS maintained a Buy rating with a $200 target.

In a note, Wolfe Research’s Alex Zukin described Palantir as a leading enterprise AI software provider, citing products including Artificial Intelligence Platform (AIP), Foundry and Gotham and a network of AI-focused forward-deployed engineers. He described the Ontology framework as the company’s “secret sauce,” explaining the layer organizes enterprise data, workflows and business relationships so AI systems operate with business context. The firm wrote that Palantir is not “Too Big to Fail” and called it “Too Big to Ignore.”

Wolfe highlighted several operating metrics: net revenue retention near 150%, year-over-year revenue growth of about 85%, backlog growth of 97% and average revenue per customer up roughly 40% year over year. Those results come from about 1,000 customers and roughly 4,000 employees.

The firm estimated Palantir’s total addressable market at about $385 billion across more than 100,000 enterprise customers. Its base-case forecast projects revenue compound annual growth of 39% from fiscal 2026 to fiscal 2029; an upside scenario projects 55% annual growth for the same period.

Analysts flagged valuation and competition as risks. Wolfe’s note valued the stock at roughly 30 times projected 2027 revenue and about 65 times projected earnings. Investors have questioned whether larger AI firms including OpenAI, Anthropic and Databricks can build deployment teams and business-context layers that resemble parts of Palantir’s Ontology.

Palantir pointed to profitability as a differentiator, reporting an 84% gross profit margin. Company management has emphasized the complexity of its operating system and stated its capabilities go beyond deploying large language models and processing enterprise data.

Analysts and investors remain divided: some cite retention and backlog metrics as signs of deepening enterprise engagement; others focus on the premium valuation and intensifying competition for enterprise AI deployments.