Palantir Platform

One of the leading European manufacturing plants uses Palantir Foundry  for manufacturing interior parts of various car brands such as Honda, Hyundai, Ford, Mercedes-Benz, and BMW. This involves highly secured information that is not supposed to be shared with any competitors.

My experience with Palantir Foundry  and Azure  has been good. Palantir Foundry is costly, but Azure  is open, which allows for easier experimentation. Being a closed product, Palantir Foundry is difficult to practice offline unless we have an enterprise edition. However, it is very secure compared to other platforms.

Palantir Foundry's best features include security, built-in features, low-code, no-code platform, and ease of use.

The collaborative workspaces within Palantir Foundry contribute to team efficiency and project outcomes through seamless operation. The ease of customization is particularly notable.

I have worked with the data lineage feature in Palantir Foundry, which comes by default. We simply need to tick the checkbox and make necessary configuration changes within the system itself. We do not need to procure another lineage platform as Palantir Foundry has its own built-in features for data lineage, data governance, and data security.

The lineage feature helps enhance our data management practices by allowing us to understand the origin of data, track all activities happening on the data, identify users and consumers, and monitor how it flows across the system. This makes it easier to generate reports based on the lineage database.

The predictive analytics capability within Palantir Foundry impacts financial forecasting strategies through its AIP functionality, which includes numerous pre-built models, LLMs, and data science application libraries. Using the AIP library within Palantir Foundry helps us develop quick resolutions for predictive models and analytics.

Apart from the pricing and offline availability issues, improvements are needed in Palantir Foundry's costing factor. Cost-wise, it is not open for everybody, and they are not exposing anything outside of the box.

The major hindrance with Palantir Foundry is that being a very closed product, the cost optimization and costing are not exposed to the end users. Apart from that, it is a very good tool and product.

In terms of stability and scalability, I have not faced any challenges. The scalability and scheduling capabilities are very good. Regarding performance, I have not experienced any stability, performance, or security issues.

I haven't had the opportunity to discuss with Palantir Foundry technical support, but we were able to manage on our own. The documentation and technical support are very good.

Positive

Palantir Foundry is an excellent product for data engineering. On a scale of one to 10, I would rate Palantir Foundry a 9.

I am getting into the ontology space using Palantir Foundry . The primary use case is for developing a common business model that includes data, people, and processes, essentially describing how businesses operate. We are applying this model in the utilities sector.

Palantir Foundry  offers the core capabilities of a digital twin enterprise. The digital twins concept allows bi-directional data and process integration between virtual and physical worlds. This integration enables what-if analysis, such as simulating tariff changes to plan responses. The low-code app development platform empowers any user to build applications using preferred visualization tools, while the AI platform allows for diverse model integration. Furthermore, Palantir Foundry is not limited to one LLM model, offering flexibility to build personalized models.

Palantir Foundry is missing marketing, which could help it grow. Additionally, the startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership. Palantir Foundry also needs to change the traditional data management approach from one-directional to bi-directional, near real-time data flow everywhere, which they address through data virtualization.

Palantir Foundry's customer service is excellent. I would rate it ten out of ten. They are knowledgeable, and their boot camps demonstrate solutions in just three days, which typically takes months or years. This speed of delivery was a key driver for choosing Palantir Foundry.

Positive

Palantir Foundry's initial setup is affected by high startup pricing, which might scare some people off. However, it is cost-effective in the long run, as it reduces the need for developers.

Palantir Foundry is expensive to start, but not costly in terms of total cost of ownership. Its high initial pricing can be intimidating, but it becomes cost-effective as it reduces the need for a development team. Traditional data management is being transformed to bi-directional, near real-time data flow using data virtualization.

I have heard about a partnership between Databricks  and Palantir Foundry. Databricks  has similar concepts focused on data.

I rate Palantir Foundry a ten out of ten. Overall, it's an excellent solution, and I recommend it. While I am building a business case to adopt Palantir Foundry, it's worth noting its partnership with Databricks. Our organization already has Databricks, and I hope we will get Palantir Foundry as well.

Our use cases are mostly related to data analytics. We are building some dashboards and ETL pipelines on the Palantir side. Palantir Foundry is a low-code/no-code platform with a user-friendly UI. It is better than Databricks, where you need to code. Palantir Foundry has better data lineage. However, Databricks also provides many features with Databricks Unity Catalog.

I like the data onboarding to Palantir Foundry and ETL creation.

The solution’s data security could be improved. We cannot use many Python packages with the solution. We were able to use only a few compatible Python packages.

I have been using Palantir Foundry for six months.

I rate the solution’s stability a nine out of ten.

We couldn't implement or use some of the latest functionalities, like Spark. Palantir Foundry is scalable, but it is costly compared to other cloud providers. The solution is more suitable for small and medium businesses. It might be difficult for large enterprises.

I rate the solution’s scalability a seven out of ten.

The solution’s initial setup is simple compared to that of other tools.

Palantir Foundry is an expensive solution. However, it works because we need to develop a little less compared to Databricks or any other environment.

I prefer Palantir Foundry for simple ETL pipelines because it is a low-code/no-code platform. I will choose Databricks for handling complex big data because it supports all the Python modules.

We tried some machine learning algorithms with Palantir Foundry. Since some packages are unavailable, we have to do that specific work on the Azure environment. I would recommend the solution to other users, but they must evaluate data security concerns.

Overall, I rate the solution an eight out of ten.

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.