The Zhitong Finance App learned that Goldman Sachs upgraded the company's software company Palantir (PLTR.US) rating from “neutral” to “buy” because of its recent poor stock price performance and rising valuation appeal.
Goldman Sachs analyst Gabriela Borges wrote in a report to clients: “We raised Palantir from neutral to buy. The target price for 12 months is $230, which means about 18% upside.” She pointed out that with Palantir's current revenue operating rate of about 8 billion US dollars and a growth rate of about 100%, investors are mainly debating two issues: first, whether the best part of Palantir's artificial intelligence opportunities has been realized, or whether the market is deep enough to support a new round of anticipated revisions; second, how sustainable is the company's FDE model.
Borges said that the main conclusion drawn from a series of recent industry exchanges is that the stock is preparing to outperform the market for another phase before 2027. It also believes that Palantir's Total Addressable Market (TAM) may be undergoing “another step change”, partly due to sovereign AI, customized applications, and the company's new vertical strategy.
Additionally, Borges explained Palantir's FDE mode. FDE generally refers to pre-deployment engineers. This model requires a closed loop of close feedback between field teams and product teams to quickly understand customer requirements and deploy solutions. In her opinion, Palantir has polished the model to “almost perfect, and can even be automated with AI FDE.”
Market participants believe that Goldman Sachs's current rating increase comes at a time when Palantir's recent performance is lagging behind and investors disagree on the high valuation and sustainability of growth of AI concept stocks. Goldman Sachs's optimistic view means that it believes that corporate AI requirements, government contracts, and vertical industry expansion may still drive Palantir into a new growth cycle. However, the report also implied two key risks: whether AI opportunities have been fully priced, and whether the FDE model can continue to be efficient even after scaling up.