Primer, a natural language processing (NLP) company, announced the launch of Primer Engines, an integrated suite of industrial-grade NLP models that bring machine learning (ML) to mission-critical operations at any organization. Primer Engines unlock advanced capabilities for commercial organizations to use in almost any text-related business application. Primer Engines make it possible for anyone responsible for data analysis, intelligence, or operations to fully access, explore, and take advantage of the firehose of text-based data coming their way. With Primer Engines, there’s no need to mobilize a team of machine learning experts to build an NLP solution from scratch. Primer’s team of ML engineers is continuously pushing the realm of what’s possible with NLP, building new domain and data-specific engines.

Organizations can pick and choose from over two dozen pre-trained Engines for the task they need, including Primer’s Named Entity Recognition (NER) model. Each engine comes with a plug-and-play API that enables integration into existing applications, tools, or systems, both in the cloud and on premises. Organizations can connect multiple Primer Engines together and build their own NLP-powered data processing pipelines that match their unique workflows. Engines can be retrained in Primer Automate, the company’s recently released no-code platform, to build and deploy custom deep learning models.