Expert.ai today announced a new version of its natural language (NL) platform featuring powerful enhancements. Combining machine learning (ML) and symbolic knowledge representation (hybrid AI), the updated platform further facilitates the design, development and deployment of language models, and accelerates production of innovative enterprise applications, through accurate language understanding at scale.
Upgrades to the expert.ai award-winning platform include:
- Knowledge Models Fortified: Built in and ready-to-use pre-trained, rules-based models now contain expanded industry, role and use-case concepts and relationships to quickly improve the accuracy of natural language (NL) projects. Other model enhancements include updated environmental, social, governance (ESG) classification and sentiment, as well as personally identifiable information (PII) extraction.
- New Solutions for Pharma & Life Science: Additional knowledge models now support solutions for drug discovery, clinical trial insights, key opinion leader identification and scientific publication insight analysis. A new preclinical report analysis solution dramatically speeds up the quality control check process of reports prior to their submission to regulatory bodies.
- AI-driven Robotic Process Automation (RPA): The only NL, hybrid platform that integrates with UiPath, Blue Prism and Automation Anywhere, expert.ai supercharges bots with unique NL capabilities only possible by merging different AI techniques. This expands the scope of intelligent process automation across tasks requiring accurate understanding of documents for email automation, contract analytics, claims, underwriting automation and customer service support.
- Expanded Deployment Options: The expert.ai Platform now supports on-premise deployments of NL workflows for organizations that want complete control over data or demand it be kept on premise for security and compliance purposes.
- New Operational Monitoring Dashboard: Delivers improved visibility to operational metrics (i.e., CPU, memory, model performance) associated with language operations (LangOps).
