The latest version of its platform includes core technology enhancements that provide organizations with even more security and flexibility when creating or enhancing AI-enabled natural language solutions, as well as security and infrastructure improvements.
Expert.ai, an AI company with its hybrid natural language (NL) platform, announced August 1 that it has expanded the capabilities of its enterprise AI platform for natural language solutions. With this, expert.ai aims to help organizations transform their processes and reduce manual activities.
The enhanced features of the expert.ai platform include stronger document format and annotation recognition (better document understanding capabilities for format detection, font recognition and extraction, and label reading), streamlined migration of existing taxonomy projects, security enhancements (with an update to Kubernetes hardening procedures), new analytics filters (with the ability to filter annotation and extraction class data for false positives, false negatives, and true positives), and optimized hybrid model performance (allowing users to deploy and run multiple hybrid models with a single linguistic engine to speed workflow and reduce computational overhead).
Marco Varone, CTO of expert.ai, explained: “The ability to extract valuable insight from language data is crucial for competitive advantage, but it’s easy to get overwhelmed when it comes to the complexity of analyzing text. By continuously advancing our capabilities, we are helping organizations transform their processes and reduce manual activities that are inherently both more error-prone and costly through natural language solutions that directly impact the business outcomes for critical enterprise processes.”
About a month ago, expert.ai launched its AI platform for insurance, that provides insurance teams with a way to automate the repetitive tasks associated with document reviews, extraction and assessments.
Headquartered in Boston, expert.ai provides a hybrid natural language (NL) platform that is built for the complexity of unstructured language data. The hybrid AI approach combines natural language understanding and processing, Machine Learning, knowledge-based AI, Large Language Models, and Intelligent Document Processing (IDP) capabilities to help companies understand the context, meaning and relationships in language.
You can find the full press release here.
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