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Palantir Platform
Palantir Platform empowers organizations to effectively integrate their data, decisions, and operations.
Reviews (71)
Jeni J.
Powerful Platform with a Steep Learning Curve
Reviewed on Aug 16, 2026
Review provided by G2
What do you like best about the product?
I like how Palantir Foundry's Ontology connects raw data with actual business objects, processes, and actions, rather than leaving everything as disconnected datasets. The experience feels especially powerful when building operational workflows and AI-assisted applications because the same context can be used by both people and AI. The platform's AI capabilities add useful automation and decision support, and its AI-powered workflows make automation and decision support practical rather than just experimental.
What do you dislike about the product?
The biggest area for improvement is the learning curve. Foundry is extremely capable, but understanding the different tools, Ontology concepts, and development patterns can take time, especially for new users. I’d also like clearer visibility into usage and costs, since compute and other usage can vary depending on how workflows are designed; once the platform is set up properly, though, the flexibility is worth it.
What problems is the product solving and how is that benefiting you?
I use Palantir Foundry to integrate data from various systems, turning fragmented information into a single connected view. The Ontology connects data to business processes, and AI capabilities automate analysis and workflows, though initial setup requires effort and expertise.
Aswindev P.
Foundry’s Ontology and End-to-End Platform Make Enterprise AI Operational
Reviewed on Aug 14, 2026
Review provided by G2
What do you like best about the product?
The standout brilliance of Palantir Foundry is how it fundamentally rethinks enterprise data architecture through its Ontology feature. Traditional data lakes and warehouses usually stop at storing information in static, disconnected tables. What I like best about Foundry is that it maps those raw tables into real-world business objects such as a specific manufacturing plant, a customer account, or a shipping route. Instead of just housing data, the Ontology captures the relationships, logic, and actions associated with those objects, creating a living digital representation of your organization. Once this semantic layer is established, every new application or workflow operates from the same unified reality, shifting the focus from simply analyzing data to actually running the business.
When it comes to what is most helpful, Foundry’s seamless, end-to-end cohesion completely eliminates the software fragmentation problem. Rather than forcing IT to stitch together separate tools for data ingestion, processing, and visualization, Foundry provides native functionality for the entire pipeline. You can bring in raw data, transform it using their Pipeline Builder, and deploy interactive applications for frontline workers using their Workshop tool, all within one secure environment. This cohesiveness has become even more powerful with the integration of Palantir's Artificial Intelligence Platform (AIP). Features like AIP Logic allow developers to create AI-powered functions and automated workflows by connecting large language models directly to the governed data in their Ontology, making the jump to enterprise AI incredibly smooth and operational.
The operational upsides of using Foundry are massive, particularly regarding governance, transparency, and development velocity. Because the platform automatically tracks the lineage of every piece of data, an executive or auditor can look at a final dashboard metric and trace it perfectly back to its original source system. Furthermore, by embedding strict security and access controls directly into the data and AI layers, organizations can safely deploy AI agents without risking unauthorized data exposure. Ultimately, the greatest upside is how the platform creates compounding value. Since every new application or machine learning model reuses the same underlying Ontology, teams can build and deploy subsequent projects significantly faster than the one before it, completely changing the speed at which a business can adapt to new challenges.
When it comes to what is most helpful, Foundry’s seamless, end-to-end cohesion completely eliminates the software fragmentation problem. Rather than forcing IT to stitch together separate tools for data ingestion, processing, and visualization, Foundry provides native functionality for the entire pipeline. You can bring in raw data, transform it using their Pipeline Builder, and deploy interactive applications for frontline workers using their Workshop tool, all within one secure environment. This cohesiveness has become even more powerful with the integration of Palantir's Artificial Intelligence Platform (AIP). Features like AIP Logic allow developers to create AI-powered functions and automated workflows by connecting large language models directly to the governed data in their Ontology, making the jump to enterprise AI incredibly smooth and operational.
The operational upsides of using Foundry are massive, particularly regarding governance, transparency, and development velocity. Because the platform automatically tracks the lineage of every piece of data, an executive or auditor can look at a final dashboard metric and trace it perfectly back to its original source system. Furthermore, by embedding strict security and access controls directly into the data and AI layers, organizations can safely deploy AI agents without risking unauthorized data exposure. Ultimately, the greatest upside is how the platform creates compounding value. Since every new application or machine learning model reuses the same underlying Ontology, teams can build and deploy subsequent projects significantly faster than the one before it, completely changing the speed at which a business can adapt to new challenges.
What do you dislike about the product?
While Palantir Foundry’s completely unified architecture is its biggest selling point, it is also its most frustrating operational downside. It fundamentally operates as a massive walled garden. If you have all your data and workflows inside Foundry, it works beautifully. However, users consistently report that getting data out of the platform or attempting to integrate it with external applications that exist outside the Palantir ecosystem is notoriously difficult and heavily restricted. You are essentially expected to build everything inside their environment, which creates a significant vendor lock-in risk. If a business decides to migrate away from Foundry in the future or wants to use an external tool alongside it, untangling the ontology and exporting the data pipelines becomes an incredibly painful and restrictive process.
Another major pain point is the incredibly steep learning curve required to actually use the platform effectively. Because Foundry uses a highly specific, proprietary way of modeling data, new data engineers and analysts cannot simply apply their standard data architecture knowledge directly; they have to completely relearn how to build pipelines the "Palantir way". This friction is heavily compounded by the fact that users frequently find the platform's official documentation to be outdated, incomplete, or unhelpful for troubleshooting. When a deeply interconnected data pipeline breaks, the error logs can be difficult to parse, and engineers often find themselves relying heavily on expensive Palantir support representatives rather than being able to debug the system independently.
Finally, the platform is extraordinarily expensive, and its closed nature means there is very little visibility into cost optimization, leaving buyers anxious about sudden licensing increases over time. It is unapologetically priced for massive enterprises, making it complete overkill for simpler, everyday data use cases. Furthermore, despite the premium price tag, the front-end application builders offer surprisingly limited customization options compared to open-source alternatives, often forcing developers to stick to rigid, predefined UI templates. Even their heavily marketed Artificial Intelligence Platform (AIP) has growing pains, with engineers noting that the AI agent still occasionally struggles to understand complex queries and can provide incorrect solutions when asked for debugging help.
Another major pain point is the incredibly steep learning curve required to actually use the platform effectively. Because Foundry uses a highly specific, proprietary way of modeling data, new data engineers and analysts cannot simply apply their standard data architecture knowledge directly; they have to completely relearn how to build pipelines the "Palantir way". This friction is heavily compounded by the fact that users frequently find the platform's official documentation to be outdated, incomplete, or unhelpful for troubleshooting. When a deeply interconnected data pipeline breaks, the error logs can be difficult to parse, and engineers often find themselves relying heavily on expensive Palantir support representatives rather than being able to debug the system independently.
Finally, the platform is extraordinarily expensive, and its closed nature means there is very little visibility into cost optimization, leaving buyers anxious about sudden licensing increases over time. It is unapologetically priced for massive enterprises, making it complete overkill for simpler, everyday data use cases. Furthermore, despite the premium price tag, the front-end application builders offer surprisingly limited customization options compared to open-source alternatives, often forcing developers to stick to rigid, predefined UI templates. Even their heavily marketed Artificial Intelligence Platform (AIP) has growing pains, with engineers noting that the AI agent still occasionally struggles to understand complex queries and can provide incorrect solutions when asked for debugging help.
What problems is the product solving and how is that benefiting you?
From a business and operational standpoint, the fundamental problem Palantir Foundry solves is the crippling disconnect between analyzing data and actually acting on it. In most large enterprises, data sits in rigid, disconnected lakes or warehouses. Leaders are handed static dashboards that tell them a supply chain is broken, but they are forced to log into entirely different ERP or CRM systems to actually execute a fix. Foundry solves this "read-only" problem by operating as a two-way digital twin of the enterprise. By utilizing its Ontology, Foundry maps raw database tables into recognizable, real-world business objects like a specific manufacturing plant or a shipping route and embeds operational actions directly into them. This benefits the business by allowing frontline workers to analyze a situation and immediately execute a decision, like re-routing inventory, directly within the platform, seamlessly writing that action back to the underlying source systems.
Another massive business problem it solves is what the industry calls AI "pilot purgatory". Companies are burning millions of dollars building impressive AI chatbots and machine learning models in isolated sandboxes, only to find they cannot deploy them safely into production because the AI lacks enterprise context and security guardrails. Foundry’s Artificial Intelligence Platform (AIP) tackles this by connecting Large Language Models directly to the governed data inside the Ontology. Because the AI automatically inherits the platform's strict access controls and semantic business logic, a company can safely deploy AI agents that actually automate complex, real-world tasks such as resolving scheduling conflicts or optimizing factory asset performance without risking data leakage or hallucinations.
Finally, Foundry addresses the lack of trust and development velocity caused by fragmented, "spaghetti" data architectures. When an organization relies on a patchwork of different integration and visualization tools, data lineage is often lost, meaning executives cannot trace how a critical metric was calculated. Foundry tracks the lineage of every single piece of data from the moment it enters the pipeline to its final dashboard visualization. Even better, because the entire enterprise operates on a shared, unified semantic model, teams do not have to rebuild logic from scratch for every new project. The direct business benefit is compounding operational velocity: once the data foundation is laid, every subsequent application, AI model, or operational workflow can be shipped significantly faster than the last.
Another massive business problem it solves is what the industry calls AI "pilot purgatory". Companies are burning millions of dollars building impressive AI chatbots and machine learning models in isolated sandboxes, only to find they cannot deploy them safely into production because the AI lacks enterprise context and security guardrails. Foundry’s Artificial Intelligence Platform (AIP) tackles this by connecting Large Language Models directly to the governed data inside the Ontology. Because the AI automatically inherits the platform's strict access controls and semantic business logic, a company can safely deploy AI agents that actually automate complex, real-world tasks such as resolving scheduling conflicts or optimizing factory asset performance without risking data leakage or hallucinations.
Finally, Foundry addresses the lack of trust and development velocity caused by fragmented, "spaghetti" data architectures. When an organization relies on a patchwork of different integration and visualization tools, data lineage is often lost, meaning executives cannot trace how a critical metric was calculated. Foundry tracks the lineage of every single piece of data from the moment it enters the pipeline to its final dashboard visualization. Even better, because the entire enterprise operates on a shared, unified semantic model, teams do not have to rebuild logic from scratch for every new project. The direct business benefit is compounding operational velocity: once the data foundation is laid, every subsequent application, AI model, or operational workflow can be shipped significantly faster than the last.
Brockish S.
Palantir Foundry is a powerful data platform
Reviewed on Aug 06, 2026
Review provided by G2
What do you like best about the product?
What I like most is how Palantir Foundry brings data from different sources into one platform, making it easier to analyze data, collaborate, and build workflows.
What do you dislike about the product?
The learning curve is steep, and some features can feel complex for new users.
What problems is the product solving and how is that benefiting you?
Palantir Foundry helps centralize data from multiple sources, streamline data analysis, and improve collaboration for better decision-making.
Tanzim S.
Palantir Foundry: Powerful, Scalable Platform for Unifying Data and Driving Insights
Reviewed on Aug 04, 2026
Review provided by G2
What do you like best about the product?
Palantir Foundry excels at bringing data together from diverse systems into a single platform, which makes it easier to analyze information, collaborate across teams, and turn findings into actionable insights. Its strong governance and user-friendly tools help streamline decision-making and support business value. The platform’s scalability, robust security model, and ability to operationalize insights through workflows and applications make it a valuable tool for driving data-driven outcomes across the organization.
What do you dislike about the product?
One drawback of Palantir Foundry is its steep learning curve, particularly for new users who aren’t already familiar with data engineering or complex analytics platforms. Although the platform is extremely powerful, setting up data pipelines, ontology models, and more advanced workflows often requires substantial training and specialized expertise. Implementation and customization can also take a significant amount of time, and the sheer breadth of available features may make the interface feel overwhelming for some users.
What problems is the product solving and how is that benefiting you?
It helps us integrate and govern data from various enterprise systems, providing a single source of truth for operational and business insights. This reduces the time spent gathering and reconciling data, improves transparency across processes, and enables teams to make faster, more accurate decisions. As a result, we've seen improved efficiency, better collaboration, and quicker delivery of business value.
Anonymous
Powerful Platform with a Steep Learning Curve
Reviewed on Jul 28, 2026
Review provided by G2
What do you like best about the product?
I find Palantir Foundry to be a very cohesive platform that can do a wide variety of operations. It's powerful enough to build whatever I need within it. I really appreciate the ontology manager; it's such an interesting concept because I haven't seen anything like that in other platforms. It allows me to convert my table into an ontology, and it connects everything directly within Palantir, abstracting all the connections for me. This feature stands out as it simplifies how objects are connected, making the process seamless.
What do you dislike about the product?
I think the advantage I mentioned before can also be a disadvantage in some cases because with Palantir, you're expected to build everything within the same platform. So if you, by any chance, have data in other places, then it could be a little hard to bring that into Palantir. Also, there is quite a learning curve. It's not the easiest platform to pick up on, so you'll need someone to walk you through it, how to build it. And because it's such a broad platform, even if there is a package already built out, if you don't know how it works, then it can be challenging to follow the lineage and figure it out yourself.
What problems is the product solving and how is that benefiting you?
I find Palantir Foundry's biggest advantage is having every part of the pipeline within it, with everything so connected. It offers native functionality from initial transformations to dashboards, making the process seamless.
Manufacturing
Powerful Integration and Security, but Pricey and Overkill for Simple Use Cases
Reviewed on Jul 28, 2026
Review provided by G2
What do you like best about the product?
The system offers fantastic data integration, connecting many systems together into a single package. This includes the Ai system which is built into the foundry rather than being an external addition. The security of the system is also top of the line.
What do you dislike about the product?
The software is expensive to license. Ongoing support is also a high price and while it is very good overall, the software is limited in its uses in simple use cases
What problems is the product solving and how is that benefiting you?
Foundry allows me to track multiple productions across various sites all in one location while also keeping me updated on all things related to the supply chain. This enables me to view any potential issues before they become a large problem as well as being able to plan according to the supply chain and not from people ideal delivery times.
Ataul Haque
Integrated data workflows have transformed unstructured documents into traceable insights
Reviewed on Jun 26, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Palantir Foundry involves upgrading some legacy applications to utilize GenAI. We are trying to implement GenAI solutions for unstructured data that we receive in large volumes. Essentially, we are attempting to read this unstructured data and convert it into a structured format, with Palantir Foundry assisting us in this process through Python transforms and related functions that utilize extracted text from the OCR process. After the OCR process, we apply some AIP logics to this text to transform it into a structured format for meeting our goals.
A specific example of how I use Palantir Foundry for this process begins with the OCR scanning process itself. We scan all the incoming PDFs, Word documents, and images, which are then transferred to our automation set within Palantir Foundry. The automation connects with Python functions, executing the necessary logic to convert incoming data into the formats we need using automation, Python functions, and the code repository in Palantir Foundry. We also utilize Insights for testing processes such as file uploads.
What is most valuable?
Among the best features offered by Palantir Foundry, I think the ontology stands out as a remarkable aspect for finding everything. From a coder's perspective, everything is integrated, including Git, development IDs, and VS Code, which makes everything seamless. You can work locally on your preferred ID or directly on the Palantir Foundry portal. The integration includes checks and builds, so all aspects are available within Palantir Foundry itself. Datasets within Palantir Foundry function smoothly, with connectors facilitating connections to any data sources, including external ones. Additionally, the automation feature allows for selective control over code functions and scheduling.
In terms of user experience with Palantir Foundry, I find it to be exemplary. It is very easy to work on, although I initially struggled to understand it as this was the first platform with so many integrated features, such as Git and the VS Code editor.
Palantir Foundry enhances my main use case by allowing us to backtrack all data through ontology, which helps in understanding the objects involved and back propagating to the root cause, aiding in visualizing the entire workflow. It allows us to track our transactions, movements, and workflows efficiently compared to other platforms, providing significant support in this area.
Palantir Foundry positively impacts our organization by being seamlessly integrated and offering easy-to-access features without the need for third-party integrations. Everything is already in place, which benefits developers and subsequently enhances managers' productivity, leading to overall organizational revenue growth.
What needs improvement?
Palantir Foundry could be improved by making some aspects or features open source, as its current pricing and accessibility pose challenges. Many potential users find it difficult to access, which could hinder tech talent from engaging with this tool.
I notice technical limitations exist, yet when we encounter issues, the Palantir Foundry support team addresses our queries promptly. However, if the team works on previously raised issues to ensure they do not recur, it would enhance overall user experience and reliability.
For how long have I used the solution?
I have recently started using Palantir Foundry, and it has been almost a year since I began.
What do I think about the stability of the solution?
Palantir Foundry is stable.
What do I think about the scalability of the solution?
Palantir Foundry's scalability is impressive as it allows us to scale up easily, reflecting its design supporting our expanding use cases without restriction.
How are customer service and support?
The customer support from Palantir Foundry is great, with fast query resolution. However, ensuring that issues do not recur in the future through effective implementation would strengthen the support experience.
Which solution did I use previously and why did I switch?
Previously, we used standalone tools and services, but after discovering Palantir Foundry, we found it intriguing enough to switch, and our experience has been positive ever since.
How was the initial setup?
Handling initial onboarding and training for Palantir Foundry has been challenging. We face difficulties in accessing resources, which prompts us to arrange training sessions with Palantir Foundry representatives. This remains a concern as we still struggle with resource availability.
What was our ROI?
Although I cannot disclose specific figures, I can confirm that we have observed a good return on investment with Palantir Foundry, facilitating role transitions within our team and ultimately saving costs and time.
What's my experience with pricing, setup cost, and licensing?
The experience with pricing, setup cost, and licensing has been on the higher side. I believe that if some features were made open source, it would improve accessibility and broaden its market reach beyond just large corporations.
Which other solutions did I evaluate?
We explored other options before choosing Palantir Foundry, but ultimately, we decided to take a chance on it, and it has turned out positively.
What other advice do I have?
For deterministic outputs, Palantir Foundry performs as expected. However, for non-deterministic results, the responsibility lies with the LLMs we use, which can sometimes affect accuracy.
Palantir Foundry integrates perfectly with other tools I use. While there may be minor issues with external sources, the integrated tools such as IDE, VS Code, and Git operate seamlessly, making our workflow much more manageable compared to standalone tools.
The performance and speed of Palantir Foundry excel when handling large datasets and complex workflows, with the Foundry dataset significantly aiding in this aspect.
I advise prospective users that Palantir Foundry is an excellent solution for enterprises, but it should become accessible to a broader range of businesses at affordable prices to expand its user base.
My overall rating for this review is 8 out of 10.
Michael Mahrous
AI workflows have transformed vendor risk checks and now automate complex finance tasks
Reviewed on Jun 22, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Palantir Foundry is to provide an assisted, AI-assisted automation chatbot for the finance team; they reside in corporate finance and they have a lot of manual repetitive work that takes up to two hours to process manually. I have automated it with AI in about under 15 minutes, which was a huge win for them, using Palantir Foundry.
A quick specific example of one of those manual tasks I automated for the finance team is their manual analysis of a vendor before they onboard the company and do business with them. They do a financial capability analysis, which involves extracting data from unstructured PDFs that come in different formats; I used Palantir Foundry to employ the Visual LLM to extract the data in a structured manner. Once I have the data structured, I can create real-time dashboards for them to analyze the vendor in under five minutes.
I mainly use Palantir Foundry to process unstructured data into a structured format for chatbots, and that saves me a lot of time to build chatbots that are accurate, reliable, and answering questions for the users accurately.
How has it helped my organization?
Palantir Foundry has positively impacted my organization with over 200 projects completed efficiently and effectively, and they are very complex projects.
While I cannot speak for other projects, I can say that on my projects, I have saved over 100 hours processing multiple different vendors, which is huge for the corporate finance team.
What is most valuable?
In my experience, some of the best features Palantir Foundry offers include a great UI that is visually appealing, simple, and straightforward. The documentation is clear, and it is very user-friendly for me; I do not have to lose myself in a rabbit hole of documentation unlike Microsoft. I am starting to get tired of Microsoft, but Palantir Foundry has been the perfect solution so far.
What makes the UI stand out for me is the Artificially Intelligent FDE, which is the Forward Deployed Engineer; it is basically an AI within Palantir Foundry that helps me get things done. I think that is the most helpful part of Palantir Foundry, and I did not even need any training; I just had to work through it myself with the FDE, and with a bit of prompt engineering, I was able to get onboard Palantir Foundry very quickly.
I appreciate that Palantir Foundry can seamlessly integrate with SharePoint, which is very helpful for enterprise work, but other than that, nothing else comes to mind.
What needs improvement?
I really cannot think of any areas where Palantir Foundry can be improved; I think it is perfect.
I believe it is already perfect with FDE, and it is just a matter of continuing to improve AI FDE and making sure that it is a number one priority tool to utilize in Palantir Foundry, because users are naturally going to be inclined to use that.
For how long have I used the solution?
I have been using Palantir Foundry for the past three months now, and it has been amazing.
What do I think about the stability of the solution?
Palantir Foundry is stable.
What do I think about the scalability of the solution?
We have yet to find out about Palantir Foundry's scalability, but I am pretty sure it is fairly scalable and should not be an issue.
How are customer service and support?
I have not dealt with customer support directly; I have interacted with representatives, and they have been very supportive.
Which solution did I use previously and why did I switch?
Before using Palantir Foundry, I used Copilot Studio.
I switched from Copilot Studio to Palantir Foundry because Copilot Studio was very inaccurate, and the documentation was not clear; overall, Microsoft was not meeting my needs.
What was our ROI?
I have seen a return on investment with fewer developers needed.
Which other solutions did I evaluate?
I did not evaluate other options before choosing Palantir Foundry; I did not have any other options.
What other advice do I have?
I find Palantir Foundry's accuracy and reliability of output to be fairly accurate; it takes a bit of trial and error. I discovered that Claude Sonnet 4.6 is the best model for unstructured data, and that is more a reflection of the model delivery companies such as Anthropic and OpenAI than of Palantir Foundry itself.
I have no idea what advice to give to others looking into using Palantir Foundry. I would rate this review a 10.
Jon H.
Data workflows have become seamless and now support rich multi-language analytics for decisions
Reviewed on Jun 16, 2026
Review provided by PeerSpot
What is our primary use case?
I use Palantir Foundry to ingest data and create visualizations for decisions.
What is most valuable?
My favorite thing about Palantir Foundry is the ability to utilize multiple different types of coding languages and the current updated documentation and help features that are in there have improved pretty significantly and make it rather friendly for use.
The scalability of Palantir Foundry is the part that I love the most. That is why I said that is where my primary focus is, trying to get data and then turn it into information and knowledge and understanding, and more importantly, getting decisions out of it. The scalability is phenomenal.
What needs improvement?
I think the things that I do not like about Palantir Foundry is not a Palantir issue so much as it is from my company side and what they have commissioned for and have not commissioned for.
With Palantir Foundry, it is a part of the user tools that they provide. Their AI Assist that they use is something I have found that sometimes I get better results for when I do need help and aid. I get better results going to outsourced AI assistance sites such as Gemini, because it seems like AI Assist, which my understanding is it is supposed to be searching and utilizing the documentation for Palantir Foundry, but sometimes it gets kind of confused in the capabilities and it will tell you, 'Oh, you can use this and do this.' And then when you try it, the system says, 'We do not support this.' Whereas I can go to Gemini and it will give me a workaround that will actually work.
For how long have I used the solution?
I have been using Palantir Foundry for about four years now.
What do I think about the stability of the solution?
I find the stability of Palantir Foundry to be extremely stable. I have had only one time period where there was any downtime that I noticed, and it was for a very short period of time. When I say short period of time, I am talking within hours, not days.
How are customer service and support?
I have contacted the technical support or customer support of Palantir a couple times.
Especially for what they are supporting and doing, I find the quality and the speed of the support to be extremely fast. I usually get within a day turnaround and the support staff are extremely knowledgeable and good at what they are doing.
Which solution did I use previously and why did I switch?
Prior to using Palantir Foundry, I used various different SAPs and ERPs where I would actually have to export worksheets and then build my own. The closest thing I would be building would be databases that just resided on my computer, and I was not using anything like Palantir Foundry.
How was the initial setup?
The initial deployment of Palantir Foundry was super simple.
It did not take me any time to fully set up Palantir Foundry because it was made available to us and it was basically already set up and rolled out by the time I got permissions to use it. All I had to do is basically create an account. Actually, I did not even do that. Someone else in my organization created the account for me with the initial setup of everything. By the time I logged in and went to use things, most of it was already initialized for me.
What about the implementation team?
Palantir Foundry requires no maintenance on my end as it is taken care of by Palantir. The only thing I ever get, and Palantir already does it, is when there are certain upgrades to transformations that I have made, they will put in the upgrades, but it requires me to actually approve them and merge them in. It is minimal work on my part. Usually I can click it and just approve it right away.
What other advice do I have?
I would rate this product a 9 out of 10.
Uttkarsh Shukla
Centralized customer onboarding data has reduced backlogs and now reveals hidden risk patterns
Reviewed on Jun 16, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Palantir Foundry was with respect to the customer onboarding process, which had been outsourced to multiple teams, and there were multiple data sets that had been outsourced to different teams. Some of the teams were third parties, which were creating a backlog and elongating the process. My job was to streamline all the data into one universe, utilizing Palantir Foundry to centralize the data and information in one place to find insights where we were having backlogs for smooth customer onboarding. My objective was to utilize Palantir Foundry's data centralization capabilities to identify backlogs and situations where we were lacking.
For example, in this process, data was coming from various teams responsible for different objectives. For onboarding a new customer, there is a process known as KYC, where we need to identify the customer's details, which are usually transferred to third parties, and some in-house KYC teams must review them. Generally, when third-party cases come to the banks, they are unable to find out why a particular customer is not being onboarded. I tried to merge the data into a central place to find out the reasons, such as why the data is not being updated from third-party sources. The information sometimes lacked advance details from third parties and other sources. Additionally, I was able to map the entities, including cases where customers were not onboarded due to specific reasons related to their past profiles with other banks. These scores were not highlighted by the sales representatives, who were told to meet targets. I was able to track these and identify the pain points of why a customer had not been onboarded or entertained by the banks.
What is most valuable?
One of the best features Palantir Foundry offers is the Ontology part. It allows mapping different data from different domains and teams into one place, creating relationships between them. For example, I was handling sales data, but there was also customer profile data, financial profile data, and previous transactions data, which I mapped in one place.
Palantir Foundry helped by creating a reporting system that was fast. Previously, we waited for at least a week, but now everything was available in one place with all insights.
Palantir Foundry's governance and security are good, which is a main aspect that people prefer. Providing online data of in-house security to clients would be beneficial amidst increasing cyberattacks. Palantir Foundry's use has been impactful as the company is a vendor for a banking client who utilized it effectively.
What needs improvement?
To improve Palantir Foundry, I would recommend integrating AI capabilities. Although AI is currently available, having simple general language query features would be useful for end-users. Palantir Foundry's unique selling point is creating a universe, which should remain, but adding a query option would be beneficial.
Palantir Foundry's reporting capabilities can also be enhanced to function more in the manner of a BI reporting tool, which would be a valuable addition.
One downside is the absence of many users familiar with the platform. The cost of using Palantir Foundry is another factor that clients consider, which I accounted for when rating the solution as eight out of ten. Palantir Foundry should address pricing to make it more competitive.
Training resources for Palantir Foundry should be increased to facilitate product growth and build a community that can expand its use.
For how long have I used the solution?
I have used Palantir Foundry for one and a half years in one of the projects for my banking client, where I worked upon the creation of pipelines in Palantir Foundry, replacing their absolute systems.
What do I think about the stability of the solution?
Palantir Foundry's scalability is such that it can handle growing data and user needs easily. The implementation was not very complicated because our in-house domain data was not that large. I did not find any issues with stability.
What do I think about the scalability of the solution?
Palantir Foundry's scalability is such that it can handle growing data and user needs easily. The implementation was not very complicated because our in-house domain data was not that large. I did not find any issues with scalability.
How are customer service and support?
My experience with customer support for Palantir Foundry is that I have not interacted with them much. I did have a single interaction when I faced an issue with my login credentials. The chat system available was helpful, and the problem was solved efficiently. It was a satisfactory experience.
Which solution did I use previously and why did I switch?
Before using Palantir Foundry, we had our in-house centralized reports, but there was no centralized system that connected different domains and data in the manner that Palantir Foundry does. This connectivity is a key benefit that Palantir Foundry brought to us.
Before choosing Palantir Foundry, we considered Microsoft Fabric as we were using Power BI. However, I found Palantir Foundry more useful and stable, leading us to choose it over the former.
What was our ROI?
Both time and money were saved since a project that would usually take six months was completed in two to three months. This allowed us to allocate time to other projects as well.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing for Palantir Foundry was challenging for us. Getting approval for pricing and setup cost was difficult. We obtained initial phase approval, but later budget requests for other projects were not accepted by the board. Palantir Foundry should reconsider its pricing strategy to become more competitive.
Which other solutions did I evaluate?
Before choosing Palantir Foundry, I truly thought of Microsoft Fabric because we were already using Power BI. In comparison to Palantir Foundry, I found it more useful, and it was stable, so we went with Palantir Foundry.
What other advice do I have?
My advice to others looking into using Palantir Foundry is that they need to be clear on what aspect they want to utilize Palantir Foundry for, whether for app development or data connection. Without a clear objective, using Palantir Foundry might not be beneficial. Those with the need to integrate different partners and domains into a common platform will find it valuable.
Palantir Foundry should provide more training resources for people who are in the market so that the product can grow. Additionally, consideration should be given to building a community to expand Palantir Foundry's use. I rated this solution an eight out of ten.