The AI engine that comes with Palantir Foundry is quite interesting. We have a lot of data from various trials and analyses. We need a machine learning and analytical feature that can push huge amounts of data into the application based on pre-set rules.

Palantir Foundry is emerging as an appealing healthcare platform. Instead of having multiple tools, we can leverage this platform for our data ingestion. The solution has a couple of modules, and we haven't evaluated the entire spectrum. We are taking it one bit at a time. I don't yet have a complete vision or impression, but the tool has served our purposes.

The AI engine that comes with Palantir Foundry is quite interesting. The solution provides good flexibility and scalability.

Palantir Foundry is very good for someone technical. The tool still needs to work on the non-technical part, where people can use its flexibility. The business user should not end up writing huge queries to get small snippets of data. The solution's visualization and analysis could be improved.

I have been using Palantir Foundry for over a month.

I rate the solution a seven out of ten for stability.

Palantir Foundry is a scalable solution. Medium-level businesses can be a good starting point for Palantir Foundry, but it is definitely for enterprise businesses.

The solution’s initial setup is very simple since it is cloud based.

Palantir Foundry has been very forthcoming, but we don't have a full picture of their roadmap and what it would be built upon. It's more of a partnership where we talk about our use cases, and their team comes and tells us about the features we can use. So, it is a work in progress.

You can connect Palantir Foundry to various LLNs like Google Bard, Llama, or OpenAI.

Overall, I rate the solution a six out of ten.

Palantir Foundry is being used for multiple hybrid cloud integrations in one of the services we provide for an existing US-based customer. It's all about getting together data from Azure and Amazon and then providing a hybrid platform through Palantir Foundry. We then provide the analytics or insights enablement for the customer.

Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration. The solution is more scalable and robust compared to other hyperscalers.

The solution's pricing is high. Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive. There could possibly be a little bit of overhead concerning the maintainability of the platform.

We started using Palantir Foundry since last year.

Palantir Foundry is a stable solution.

Palantir Foundry is a scalable solution. We are supporting the implementation of Palantir Foundry for at least three or four customers who have chosen to go ahead with it.

The solution’s pricing is high.

Palantir Foundry is a cloud-based solution. I would recommend Palantir Foundry to other users based on their use cases, the complexity, and the scale of the platform they're looking for. Palantir Foundry has all the right ingredients in terms of the overall data platform, but it depends on the kind of use cases that customers are looking at.

Overall, I rate Palantir Foundry a seven to eight out of ten.

Our company uses the solution as a big data lake for storage and cherry-picking data sets using multiple languages. We create ETL pipelines, run them on a schedule, and export the data to visualize it. 

We perform functional tests on the data sets using Excel in a Fusion Sheet. A schema is created that shows all data in columns and can be manipulated to extract meaningful information. 

The Code Workbook is used to import data and write code using R, Python, Spark SQL, or PySpark. From there, you can perform calculations and create data sets. 

Contour is the graphical user interface that gives us the available basic or automatic operations. You do not need a technical grasp because it is easy to use with knowledge of the basics and filters. 

Across our company, there are 3,000 users who access our data lake. 

The Code Workbook gives you the option to switch across built-in languages such as Spark SQL, PySpark, R, or Python. 

Live video sessions enhance the available documentation and allow you to ask questions directly. There are a multitude of sessions within each framework that occur weekly. At the end of a session, you have the option to read other user's questions or ask questions yourself. 

The GUI is easy to use and does not require advanced technical knowledge. 

There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers. It is easy to find answers for code issues because Spark SQL and Python have wide user bases. There is a certain probability you won't find a solution-specific answer if you search for it. For example, there are certain errors that are specific to the solution. The more you use the solution, the more you understand it. The learning curve could be reduced with online documentation that includes the meaning of and troubleshooting for error codes. 

Predefined code templates or informational prompts would help with writing syntaxes. 

I have been using the solution for fourteen months. 

The solution is very stable. On occasion, we receive an error but it is rectified within a few hours. 

We create use cases that do not have processing limits. The solution is a big data tool so should handle any scalability. 

I have not needed technical support. 

I previously used Microsoft SQL which is a traditional database. The solution is an advancement because it is a direct jump to a big data source. 

Comparing the solution to traditional databases is liking comparing an apple to a banana.

A different team handles the solution and our data lake so I don't have knowledge of the setup. Our team accesses the solution via a web link and creates use cases. 

The solution has many features but I am only using the Code Workbook and Contour. Another feature called Slate allows you to create websites or record user data. 

Based on my current usage, I rate the solution a seven out of ten.