In the fast-evolving worlds of intelligence analysis and machine learning, organizations are constantly on the lookout for powerful yet affordable solutions.
DataWalk presents itself as a viable alternative to Palantir Gotham, offering similar capabilities at a significantly lower cost while also providing a powerful Machine Learning facility.
DataWalk’s core functionality lies in its ability to import and consolidate data from various internal and external sources into a single, integrated knowledge graph.
This enables users to organize data into understandable categories such as people, phone calls, transactions, and anything else .
To ensure an accurate view of connected, consolidated data, DataWalk supports a powerful entity resolution facility. DataWalk facilitates comprehensive analysis through tools like visual querying, link analysis, machine learning, and geospatial analysis.
These capabilities are essential for organizations that rely on extensive data analysis to drive their operations and decision-making processes.
Designed with scalability in mind, DataWalk can handle vast amounts of data, making it suitable for large-scale operations.
The platform supports collaborative investigations and data sharing, allowing multiple users to work together seamlessly, share insights, and build on each other’s findings. DataWalk is sufficiently easy to use that less technical users can effectively use the system.
These capabilities ensure that both analysts and other users across the organization can contribute effectively to investigative and analytical processes.
DataWalk’s Machine Learning facility supports an end-to-end Machine Learning process in a single platform, accelerating time to production results, and enabling delivery of better results. DataWalk also excels in its support of Large Language Models (LLMs).
DataWalk integrates with various LLMs, and the knowledge graph makes a significant contribution towards ensuring that your LLMs deliver accurate results.
A key differentiator for DataWalk is its open system design. This design allows for seamless integration with other systems, whether they are upstream or downstream in the enterprise workflow.
This interoperability is crucial for organizations that need to connect various data sources and systems to create a cohesive data analysis environment.
The DataWalk App Center further enhances this flexibility by enabling the integration of machine learning models, custom scripts, and specialized open-source software modules.
These integrations allow organizations to customize the platform to meet their specific needs without requiring extensive custom development.
DataWalk’s business model is another significant advantage over Palantir. Unlike Palantir, which relies heavily on a services-intensive model, DataWalk is Commercial Off The Shelf Software (COTS).
This approach maintains a single code base and ensures that new software updates are released roughly every quarter. As a result, all customers benefit from the latest enhancements and features without incurring additional costs for custom development.
DataWalk also empowers its customers to perform tasks such as modifying the data model and connecting new data sources themselves, reducing the need for ongoing professional services.
Cost is a major factor where DataWalk excels.
The starting price per server core for DataWalk is $43,000, which is a fraction of Palantir Gotham’s price of $141,000 per core. This significant cost advantage makes DataWalk an attractive option for organizations looking to provide powerful intelligence analysis and machine learning capabilities, at a price point consistent with their budget.
This cost-effectiveness, combined with frequent product enhancements and a customer-friendly business model, positions DataWalk as an excellent choice for organizations seeking an alternative to Palantir.
In summary, DataWalk provides a robust, scalable, and cost-effective solution for intelligence analysis and machine learning.
Its ability to integrate and analyze vast amounts of data, support collaborative investigations, and seamlessly interoperate with other systems makes it a versatile choice for organizations in intelligence analysis, fraud detection, anti-money laundering, and other applications.
The significant cost savings and flexible business model further enhance DataWalk’s appeal, offering a practical and powerful alternative to Palantir Gotham.
