AI Custom Apps

The Problem

Are Large Language Models or their popular conversational chatbot versions enough for developing your custom AI apps? 

  • What is more cost-effective for you - developing on your own using large language models or contacting Nowigence with its ready to customize extractive and generative AI techniques, including machine learning and natural language processing?
  • Is delivery on-time and on-budget add value to you?

Situation

When Mr. Cyril-Vincent Michaud, CEO of Crossover Media & Design, asked his team to evaluate AI tools and Large Language Models (LLMs) like ChatGPT, Gemini, Perplexity, and others to find the best fit for their upcoming creative story-telling app called Guppy Stories, they chose the AI toolkit developed by Nowigence.

The Solution

The Crossover Media & Design team uploaded many children’s stories during the trial period on the Nowigence platform called researchwork.ai (previously called Lille.ai). Right off the bat, they secured 60 to 95% accuracy (starting accuracy varies depending on the domain) in entity extraction clustered under the right heading.

  • Researchwork.ai has an in-built functionality where it is able to cluster entities using an unsupervised model into what the team from Nowigence calls 7Ws (Who, What, Where, When, Why, How, and How Much).
  • Selecting a few of the W’s from the drop down menus helps in information retrieval (IR) of the selected few stories..
  • IR from the selected few stories is in the form of extracted sentences and ideas.

Nowigence met Crossover’s team custom app specifications on time and on-budget.

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