Multiple Tailwinds Support Palantir's Growth Projection
We are raising our fair value estimate for the narrow-moat company.
We believe narrow-moat Palantir Technologies PLTR has a few tailwinds that support a higher growth projection. On Feb. 8, Palantir and IBM announced that Palantir’s software would be generally available on IBM’s hybrid-cloud data and artificial intelligence platform starting in March. With Palantir’s relatively small sales team, we believe this greatly expands the reach of Palantir’s software and could be a potent accelerant for customer adoption. This relationship comes recently after Palantir announced its expansion of software modules that can hasten the adoption curve for particular use cases. We believe the modules, the added no-code and low-code functionalities of the software, and expanding channel partnerships can proliferate its software into multiple industries as well as varying organization sizes. In turn, we expect a higher growth trajectory in the coming years and are raising our fair value estimate to $18 from $13. Shares traded above $38 in intraday trading, and we recommend a wider margin of safety before investing.
The Palantir and IBM partnership unifies disparate data with the ability to run simulations to understand the impact on business outcomes. The companies will be using their data science teams to assist customers as needed, and we think Palantir greatly benefits from IBM’s scale. We expect digital twin modeling, or running digital scenarios of physical infrastructures and connections between items, to be a key adoption driver. Times of uncertainty have typically been good for Palantir’s business and we believe that the pandemic may have caused organizations to rethink how to operate during times of disruptions and potentially operate at a higher level during normal circumstances. By morphing into a software-based solution from a previously consulting-led operation, Palantir can be easily adopted by organizations that may want to forgo expensive, multiyear data operation projects but are struggling with extracting insights from their data.
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