Discover how NewSci improves company systems and processes
Success with AI begins with data. Our data engineers and data scientists are experts at wrangling clients’ internal and external data to make their projects possible. By analyzing the data’s source, type, and integrity, our machine learning experts will identify the optimal algorithms for your use case. From deep data analysis, extraction, and cleansing to auto-labeling, NewSci ensures your data is ready for AI.
Recent Project: An international organization needed to analyze decades of data housed in multiple systems to determine if it was ready for natural language processing. NewSci’s AI-Data Readiness service gave the organization a field-level view of their vast datasets; identified data quality issues; missing data; data correlations; and performed initial NLP work to confirm there were significant actionable insights to be found.
Bringing an AI-powered product or service to market is nothing like traditional software-based applications. The first step is validating your product or services fit with AI to ensure not only that AI can accomplish your goals, but also confirm there are not less demanding ways to do it. Once the fit is confirmed, we create a prototype to help clients further validate their idea. Finally, we design and build a market-ready platform to support the product or service.
Recent Project: Call Simulator™ is our proprietary simulation platform designed to deliver on-demand call center training. We began by working closely with subject matter experts, using them to validate our work as it progressed. NewSci has deep technical and business experience because we know one without the other makes successful AI nearly impossible to achieve.
AI requires a sophisticated cloud infrastructure capable of handling dynamic data; high volume computational processes; and on-demand delivery of insights. NewSci’s cloud architects have built platforms capable of supporting real-time applications utilizing multiple microservices. We know providing insights at scale requires more than just a good model — it requires the infrastructure to reliably deliver them.
Recent Project: A company needed to dramatically scale their graphic design capabilities to support a global ecommerce platform. NewSci Labs created an end-to-end AI-powered process which included the use of machine learning; deep learning; and computer vision. Concurrently, we built the cloud infrastructure to deliver the service in real-time to end-users.
Do you have an idea for a project?
Machine learning projects can be stated clearly by outlining three concepts. They are succinctly summarized in an abridged quote from Tom M. Mitchell’s 1997 Machine Learning book.
“A computer is said to learn from experience with respect to a task and performance measure, if its performance at that task improves with experience.“
Complete the form below to submit your project to the NewSci Labs team for consideration!