Why Palantir (PLTR) AIP Is Important As AI Move Into Decision and Inference Phase

Traditionally, data analytics or analysis are generally being handled by the statistics part, but if we were to go down that path, even the most sophisticated ML model is an expensive guessing game without data analysis.

So what is the data analysis important in the AI journey and how Palantir AIP platform could be a trusted solution to help business to look at this crucial yet often overlooked aspect of machine learning and understand the importance of data analysis for building robust, reliable, and ethical AI.

We need to start by first working on data to train an ML model. Raw data, if used as is, can introduce errors and inaccuracies in the model, and this can be a big risk in the long term if these errors go unnoticed in the testing phase.

As per the Data Trust Survey, 82% of companies believe data quality concerns are a barrier to successful implementation, and 50% reported data quality in their organization as the #1 issue for data integrity concerns.

Data analysis acts as the bridge that connects raw data with actionable insights, transforming chaotic numbers into a roadmap for intelligent decision-making. Analysts gain crucial insights that form the bedrock of informed choices in ML algorithms by dissecting raw data.

Palantir's future growth prospects are going to hinge largely on how well AIP does. The company has been investing aggressively into its growth by launching boot camps with prospective customers to uncover opportunities where the platform can help them, which can lead to conversions and greater revenue growth down the road.

"Palantir's AIP platform has strong capabilities across data ingestion and preparation, with intuitive user interfaces and automation," Forrester said.

The positive assessment of AIP not only helps communicate to investors the strength of the overall platform and what it offers, but it can also entice buyers who are looking for an AI platform to choose Palantir, knowing that it may offer a better option for their needs.

As we can see that as AI move into the inference phase, the data part still stayed and data analysis and analytics are still ongoing, reason is because there are new datas being feed into the model as the training of the model continue.

Artificial Intelligence (AI) is transforming the business landscape, with 9 out of 10 businesses already investing in the technology, as per a report by Tidio. The number of businesses using AI has also grown by 300% in the last 5 years, making it more important than ever before.

It would be an understatement to say that AI is now indispensable for most organizations. The core of this incredible technology lies in its algorithms and contextual understanding of data, which Machine Learning (ML) models define. ML algorithms and frameworks often steal the spotlight, but beneath the surface of it all is a silent powerhouse - data analysis.

Palantir Technologies has developed an artificial intelligence platform that can help companies automate processes and enhance their decision-making. An advisory company, Forrester, ranked Palantir's platform as the best, even when compared against offerings from big tech giants.

Actually we can look at it as a platform which allows the bringing together of multiple data sets, analytics, and AI techniques in a composable manner. So there are many data analysis or analytics tools out there, and why Palantir should be looked at a Decision Intelligence Platform?

Organizations can reimagine decision-making processes in the increasingly complex, disruptive, and competitive business landscape with the help of DIPs. If you do not align with your business strategy or stakeholders' objectives, it is likely that your investments in foundational data technologies will yield few valuable business outcomes.

Here is what Palantir does (taken from Palantir website on the functionality), if we were to mapped it to Decision Intelligence, Palantir is not just any data analysis or analytics tools.

AIP's AI functionality can be divided into three categories:

AIP Assist:An LLM-powered support tool designed to help users navigate, understand, and generate value with the Palantir platform. Users can ask AIP Assist questions in natural language and receive real-time help with their queries.

AIP assistant features in platform applications:Native LLM-backed features designed to help end users perform regular workflows in the Palantir platform. These are highly-specific features that leverage knowledge of the platform to accelerate a user's day-to-day operations.

AIP capabilities for custom workflows:A set of capabilities that allow developers to build their own LLM-backed workflows or applications. These are open-ended functionalities built for developers or data scientists.

AIP has helped Palantir's growth rate hit a new gear in recent quarters. But that was not the case couple of years ago, Palantir's business was showing signs of slowing.

But after Palantir launches AIP, the company's growth rate has been taking off. Palantir’s Q2 FY24 quarterly revenue hit a record of $678M. At more than 27%, its growth rate is now around where it was two years ago.

So now the question is if the latest report can help win over more customers who may be on the fence about Palantir's AI solutions, that can potentially result in this growth rate accelerating even further.

Which I believe that Palantir could win more and more customers who have been experimenting with other DI platform and will come to realise that Palantir might be something that they need.

Using the MTF and in my earlier article, we are on track to have PLTR move above $40. And we are seeing a potential MACD bullish crossover.

With PLTR trading above both short-term and long-term MA, with MTF giving a strong upward trend, I believe there are much more upside coming for PLTR.

I am holding onto my Palantir position as I foresee there would be more upside as organizations begin to identify the suitable platform to bring their AI journey to the next phase.

As the AI development cycle moves into inference phase, organizations are now looking at how to make use of their existing data to help them make informed decisions, this is important as that could help to reduce the time for training and hence, the inference would be much more accurate.

I believe there are more demand for Palantir AIP as they are a matured platform and could help organization to reduce the cost of trying to make decision intelligence before they embark on training an AI model with their data.

Appreciate if you could share your thoughts in the comment section whether you think Palantir would have much more upside as we move into a new phase of the AI development cycle?

Disclaimer: The analysis and result presented does not recommend or suggest any investing in the said stock. This is purely for Analysis.