Expert.ai announces the release of new features for its Natural Language (NL) platform enhancing purpose-built natural language processing (NLP) workflow support. By employing a hybrid approach that combines in NL techniques – including machine learning and knowledge-based, symbolic AI – the expert.ai Platform gets the most out of unstructured data, like text in documents, applications and tools, to enable organizations create new business models, accelerate time to value and optimize processes. Natural language text understanding has advanced to among the most widely embedded AI capabilities within organizations.

NLP is no longer considered experimental, but a crucial technology for creating tangible ROI and achieving competitive advantage, and hybrid NL is becoming the de-facto approach to optimize results. According to Forrester*, "Hybrid AI delivers the best results for NLP Applications. Human knowledge remains essential for many use cases, including the effective use of natural language processing (NLP)." Expert.ai's hybrid NL Platform analyzes and understands unstructured language data in vertical domains to accelerate business impact.

Experience with hundreds of clients across the insurance, financial services, life science/pharmaceutical, healthcare and publishing and media verticals use NL to create competitive advantage via undervalued language data within their enterprises. Enhanced on-premise deployment options and taxonomy management are among the major updates. Deployment (on premise installation): With the expert.ai platform, organizations can accelerate their AI initiatives while fully managing the performance, security and scalability of their data and infrastructure.

The new release also enables the use of Kubernetes (K8s) to store core data on-premise, implement specific security measures or comply with specific regulatory requirements while accessing the latest updates to remain current. Taxonomy: The new platform release offers the possibility of adding 3rd-party external knowledge sources to deliver NL applications to production faster with higher levels of business accuracy. Third-party knowledge sources include Unified Medical Language System (UMLS) like MeSH, ICD9 and ICD10 and specific resources like the ones provided by WAND Inc., the premier source for industry vertical taxonomies, business taxonomies and specialty domain-specific taxonomies.

Additional features include: APIs: Developers can now interact with expert.ai APIs using visual documentation, making it easy for back-end implementation and client-side consumption. Development teams can now visualize and interact with the API resources using a familiar Swagger interface. Navigation of Knowledge Graphs (KGs): Resulting in customized navigation of knowledge models to quickly identify the strength of related concepts and connections.

Expert.ai Platform users can now navigate all KGs within the Platform and in particular: different technical versions of Knowledge Graphs; Knowledge Graphs for CPKs in different models; Knowledge Graphs that are part of experiments run within the authoring environment; Knowledge Graph CPKs derived from the building of a Knowledge Graph Editor project.