Expert.ai Recognized by Leading Research Firm as a Strong Performer in Text Analytics Platforms Evaluations

The leading company in artificial intelligence (AI) for language understanding expert.ai was among the select companies that Forrester invited to participate in The Forrester Wave: Text Analytics for both People-Oriented and Document-Oriented Platforms.

In their 26-criterion evaluation of document-oriented text analytics platforms, Forrester identified the 12 most significant platforms in the market; their 29-criterion evaluation of people-focused text analytics identified the 13 most significant platforms. In both reports, expert.ai was named as a Strong Performer, receiving the highest scores possible in eight criteria, including data enrichment and labeling, support for relevant use cases, knowledge-based AI, subdocument text analytics, document-level text analytics, natural language inference (People-Oriented), DevOps, and architecture and deployment options.

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“When enterprises want to put NLP solutions into production—not just as experiments, but real solutions—they need to go beyond traditional tools, single techniques and over-hyped language models,” said Luca Scagliarini, expert.ai CPO. “We believe this recognition by Forrester shows that the market is beginning to align with our vision, which is based on providing the most effective mix of natural language tools and techniques to address all of your strategic business use cases within a single, purpose-built NLP platform.”

According to both Forrester reports, “Expert.ai is a great choice for customers looking to build customized text analytics applications using hybrid AI (the combination of knowledge/symbolic and machine learning techniques), or customers looking to leverage knowledge-based AI for out of the box accuracy, model explainability (a key in highly regulated industries), or who are not ready to invest in the full ModelOps cycle.” The company also received the highest score possible in the planned enhancements criterion within the strategy category in the Document-Oriented Wave.

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