Mosaic Data Science has developed a solution framework to help organizations build a secure neural search engine that automates the laborious task of combing through millions of documents securely behind their firewalls. As a recognized leader in AI & ML, we have deployed hundreds of successful, reliable Neural Search analytics solutions that yield targeted query results in seconds.
Mosaic announces our newest framework: custom Neural Search Engines using LLMs & GenAI that can save thousands of hours reviewing documents.
Mosaic helped a North American provider of international freight forwarding services build an NLP solution that automates the tariff classification process, saving valuable resources and reducing risk while improving the customer experience.
Mosaic dives into our latest solution framework, The Neural Search Engine. Our tool can be tuned to ingest any set of documents and return relevant information in seconds. We leverage the retriever/reader architecture where for a given question, related context is obtained from the enterprise-specific knowledge base and fed to deep learning models.
In this Q&A with Sean Osis & Juan Rebollo, we discuss hot-button topics like GenAI, what is hype, and what has potential for innovation.
Mosaic built a custom voice search solution using deep learning and state-of-the-art language models to intelligently parse complex mechanical operation manuals and return the desired search results
Contextual search can be labeled as a search capability that focuses on the context of the user-generated query including the original intent of the user to show the most relevant set of results. It is quite different than traditional search technologies which focus only on keyword matching.
Mosaic used NLP algorithms to automatically extract various insights about people calling into a customer call center. We created a process to identify at-risk customers that called the previous day based on the transcript of the call.
Text data presents a tremendous opportunity to benefit all stakeholders of an organization – investors, employees, processes, and the all-important customer – if the organization can find a way to sift through this data in an automated way to extract key information and solve specific challenges. In that case, they could learn about their firm and start optimizing the way they operate.
For one of the US’s largest healthcare systems, Mosaic designed and deployed a custom machine learning tool to identify anomalous purchase orders.