integrates composite AI techniques into its platform to deploy natural language-based applications – aims to facilitate and accelerate the integration of natural language processing into artificial intelligence systems. It announces a new version of its specialized platform, Platform, combining artificial intelligence and machine learning to transform language into data, analyze and understand complex documents, accelerate intelligent process automation and improve decision-making. of decision.

By extending the core capabilities of its solution and adding new features, such as out-of-the-box knowledge models and connectors, the new version of the platform increases flexibility, simplifies integration and optimizes development pipelines. data in order to increase the efficiency of all processes involving natural language. “To scale quickly and make AI investments pay off, organizations need the tools and capabilities to get real results, faster. is at the forefront of efforts in the field of composite, or hybrid, AI, thanks to its market expertise and best practices, developed by hundreds of successful implementations, in sectors such as insurance, financial and banking services, publishing and media, defense and intelligence,” explains the publisher.

A combination of different AI techniques

Designed specifically for AI applied to natural language, the platform leverages the combination of different AI techniques (Machine Learning and rule-based symbolic understanding) with an accessible authoring environment to support the entire natural language processing flow. It is based on the principle that no AI technique in natural language can respond perfectly to all projects.

The features of the new version of the hybrid AI platform are as follows:

  • smarterfrom the start knowledge models bring NL applications to production faster with higher levels of accuracy. The new version of the platform includes access to customizable and pre-built rule-based NLP knowledge models used to classify text and extract domain- or use-case-specific entities, ideas and relationships . The knowledge models made available by the new version of the platform include: finance (commodities, currencies, macroeconomics); ESG (environment, social and governance); life sciences ; behavioral and emotional traits; PII (Personally Identifiable Information, Redacted or Pseudonymized);
  • Simplified deployment process in multiple environments including Azure: The new release allows users to select MS Azure as their preferred deployment environment;
  • Easier integration, out-of-the-box connectors: More insights to discover with hundreds of connectors through the Boomi integration platform and Qlik connectors, which provide fast and secure access to natural language resources of systems and third-party apps;
  • Natural Language Operations (NLOps) enhancement allows the inclusion of custom Python and Java scripts or third-party services for pre- or post-processing activities in NL workflow orchestrations.

According to Gartner, “The era of unique AI techniques is coming to an end. Software and service providers that are unable to offer solutions that combine multiple AI techniques (such as machine learning, rule-based systems, optimization techniques, knowledge graphs, natural language) will quickly find themselves at a disadvantage compared to those who can. Introducing composite AI techniques, even within existing products, will have a profound impact on their capabilities.”

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