In the realm of intelligence analysis applications, DataWalk emerges as a formidable alternative to Palantir Gotham, offering robust capabilities at a fraction of the cost. Notably, DataWalk’s approach isn’t just about technological innovation; it also embodies a distinct business philosophy and model that differentiate it from Palantir.
When we talk about a “Palantir alternative,” we refer to a central “database” equipped with intelligence analysis facilities. DataWalk excels in this capacity, providing an excellent substitute for Palantir Gotham. Additionally, for specific scenarios like machine learning operations infrastructure, DataWalk can also serve as a viable alternative to Palantir Foundry.
DataWalk can import data from various internal and external systems, consolidating and connecting this information within a single knowledge graph. This ability allows DataWalk to pull data from numerous applications or data silos, connecting and reorganizing it into an aggregated view based on understandable entities such as individuals, phone calls, transactions, and anything else. To ensure an accurate view of connected, consolidated data, DataWalk includes an advanced facility for entity resolution.
Designed to handle vast amounts of data, DataWalk allows for visual querying, link analysis, geospatial analysis, machine learning, entity extraction, and other advanced analysis techniques. It also supports collaborative investigations, and is suitable not just for analysts but for other users across an organization.
DataWalk is an open platform designed to interoperate seamlessly with other systems, both upstream and downstream. While it can function as a standalone system, it’s also intended to support an automated enterprise workflow effectively. The DataWalk App Center enables the integration of machine learning models, custom scripts (developed by DataWalk, partners, or customers), and special-function open-source software modules.
DataWalk and Palantir, despite having similar capabilities, differ significantly in their business models. DataWalk’s model is not services-intensive, focusing on providing Commercial Off The Shelf Software (COTS). This approach ensures a single code base, with new software releases about once a quarte, and makes all enhancements available to all customers. This strategy reduces the need for ongoing professional services, enabling customers to handle more tasks independently, such as modifying data models and connecting new data sources.
Importantly, DataWalk offers a substantially lower price point. For example, the price per server core for DataWalk starts at $43K, whereas Palantir Gotham’s GSA price per core is approximately $141K. This price disparity is significant, making DataWalk an attractive option for organizations looking to manage costs effectively while still taking advantage of advanced software technology.
DataWalk includes a Machine Learning capability that supports an end-to-end Machine Learning process in a single platform, accelerating both time to production results and delivery of better results. DataWalk also helps to optimize capabilities of your Large Language Models (LLMs). DataWalk integrates with various LLMs, with the knowledge graph helping to ensure that LLMs deliver the most accurate results.
With DataWalk, you own your data and analyses. Any algorithms created within the platform are transparent, allowing clear visibility into risk scoring or other calculations. DataWalk does not supply private data; instead, customers use their data, ensuring transparency and control. The platform also supports granular security, ensuring excellent performance and data access control. Critically, the data and analyses belong to you, not to the vendor!
For organizations that appreciate Palantir’s capabilities but are deterred by its cost, DataWalk presents a compelling alternative. Offering predictable ongoing costs, frequent product enhancements without custom development fees, and a robust suite of intelligence analysis tools, DataWalk is a smart, cost-effective choice for modern intelligence analysis needs.