Palantir Apollo Integrations

Foundry is a transformative data platform built to help solve the modern enterprise’s most critical problems by creating a central operating system for an organization’s data, while securely integrating siloed data sources into a common analytics and operations picture. Palantir works with commercial companies and government organizations alike to close the operational loop, feeding real-time data into your data science models and updating source systems. With a breadth of industry-leading capabilities, Palantir can help enterprises traverse and operationalize data to enable and scale decision-making, alongside best-in-class security, data protection, and governance. Foundry was named by Forrester as a leader in the The Forrester Wave™: AI/ML Platforms, Q3 2022. Scoring the highest marks possible in product vision, performance, market approach, and applications criteria. As a Dresner-Award winning platform, Foundry is the overall leader in the BI and Analytics market and rated a perfect 5/5 by its customer base.

NetOwl EntityMatcher offers a reliable, swift, and expandable solution for identity resolution, taking into account not just the similarities in entity names but also critical attributes like date of birth, place of birth, address, and nationality. Additionally, it allows for identity resolution using social network details, including information about an individual's employer, spouse, or associates. Utilizing its proprietary search and indexing engine, NetOwl can combine evidence from various entity record attributes, providing a highly effective, scalable, and user-friendly approach to matching. Users can define application-specific business rules that dictate which combinations of record attributes need to be matched and establish the importance of each attribute. Furthermore, by incorporating our machine learning-driven multicultural and multilingual name matching solution, NetOwl NameMatcher, the system enhances the sophistication of name matching across different types of entities. This integration ensures that identity resolution maintains a high level of accuracy and adaptability in diverse scenarios.

NetOwl Extractor provides exceptionally precise, rapid, and scalable entity extraction across various languages through the use of AI-driven natural language processing and machine learning techniques. This named entity recognition tool can be utilized both on-site and in the cloud, facilitating a wide range of Big Data Text Analytics applications. Supporting over 100 distinct entity types, NetOwl presents a comprehensive semantic ontology for entity extraction that surpasses conventional named entity extraction tools. Its offerings encompass individuals, numerous organization categories (such as corporations and government entities), diverse geographic locations (including nations and cities), as well as addresses, artifacts, phone numbers, and titles. This extensive named entity recognition (NER) serves as a crucial basis for more sophisticated relationship and event extraction processes. The software is applicable across various sectors, including Business, Finance, Politics, Homeland Security, Law Enforcement, Military, National Security, and Social Media, making it a versatile choice for organizations seeking in-depth textual analysis. Furthermore, its adaptability to different environments ensures that users can effectively harness its capabilities to meet their specific needs.

NetOwl TextMiner merges the acclaimed NetOwl Extractor with Elasticsearch to deliver an innovative text analytics solution. This software harnesses the full spectrum of NetOwl's functionalities, making it perfect for conducting "what if" analyses, performing discovery tasks, facilitating quick-response investigations, and carrying out thorough research. By incorporating all the text analytics features of the NetOwl Extractor—including entity extraction, relationship and event extraction, sentiment analysis, text categorization, and geotagging—TextMiner presents a comprehensive text mining platform. The results generated by the Extractor are stored within Elasticsearch, which offers a range of intelligent search and analytical capabilities. The synergy between Elasticsearch and NetOwl ensures rapid and scalable real-time text analysis suited for handling Big Data. Furthermore, the user-friendly web-based interface of TextMiner can be easily configured to accommodate various analytical needs, enabling users to swiftly access only the most valuable insights from extensive text datasets. This adaptability not only enhances usability but also allows for more tailored analysis across multiple domains.

NetOwl NameMatcher, recognized for its excellence in the MITRE Multicultural Name Matching Challenge, delivers unparalleled accuracy, speed, and scalability in name matching solutions. By employing an innovative machine learning framework, NetOwl effectively tackles the intricate challenges of fuzzy name matching. Conventional methods like Soundex, edit distance, and rule-based systems often face significant issues with precision, leading to false positives, and recall, resulting in false negatives, when confronting the diverse fuzzy name matching scenarios outlined previously. In contrast, NetOwl leverages a data-driven, machine learning-based probabilistic strategy to address these name matching difficulties. It automatically generates sophisticated, probabilistic name matching rules from extensive, real-world multi-ethnic name variant datasets. Furthermore, NetOwl employs distinct matching models tailored to various entity types, such as individuals, organizations, and locations. To add to its capabilities, NetOwl also integrates automatic detection of name ethnicity, enhancing its adaptability to the complexities of multicultural name matching. This comprehensive approach ensures a higher level of accuracy and reliability in diverse applications.

Skywise represents a cutting-edge aircraft solution powered by the expertise of Airbus and the data analytics capabilities of Palantir Technologies. By merging in-flight data, engineering insights, and operational metrics within a comprehensive analytics framework, Skywise equips airlines with a robust data platform to effectively tackle challenges in aircraft operations. This platform empowers operators around the globe to enhance the aircraft experience through data-driven insights while making informed and sustainable operational decisions. Furthermore, the integration of the Airbus Skywise Core Platform with S.FP+ marks a significant advancement in the digital transformation of technical operations, steering organizations toward a more data-centric approach. This cohesive solution is designed to foster collaboration among technical operations teams, optimize aircraft dispatch, predict unscheduled events, and bolster fleet reliability, all based on extensive sensor data collected during flights and integrated with maintenance records. Ultimately, Skywise aims to revolutionize the aviation industry by leveraging data to streamline processes and enhance overall performance.

All enterprise data must be integrated, managed, secured, and analyzed. Data is a valuable asset for organizations. There is a lot of it. Structured data such as log files, spreadsheets, tables, and charts. Unstructured data such as emails, documents, images, videos, and spreadsheets. These data are often stored in disconnected systems where they quickly diversify in type and increase in volume, making it more difficult to use each day. People who depend on this data don’t think in terms if rows, columns, or just plain text. They think about their organization's mission, and the challenges they face. They want to be able to ask questions about their data, and get answers in a language that they understand. The Palantir Gotham Platform is your solution. Palantir Gotham combines and transforms any type of data into one coherent data asset. The platform enriches and maps data into meaningfully defined objects, people, places, and events.