PREDICTIVE MODELING
SOLUTIONS
PREDICTIVE MODELING
SOLUTIONS
Cutting edge AI technology, expert domain knowledge, and passionate data scientists set us apart. Our proven integration process brings it all together.
AI Platform
Enterprise AI technology for small to mid-sized businesses
Scale
Our AI platform can be deployed at the enterprise level but is also scalable to be effective for a smaller company. Our passion is helping small to mid-sized businesses with limited data experience, technological resources, and personnel achieve their business missions through data science innovations. We take the hassle and complexity out of AI so that you can focus on what your business does best.
Accuracy and Precision
The intersection of technology and seasoned data science professionals ensures that our clients get the most accurate and precise modeling solutions available. It also ensures that those solutions are customized to their specific business problems.
Automation and Speed
A key benefit of Rapidminer's AI platform is the increased speed and reduced costs that come along with process automation. Whether your goal is reducing the amount of manual data entry and error checking in structured or unstructured text, or the efficient deployment of models and the measurement of their impact, newData's data science team can leverage the full automation capabilities of our AI platform.
AI Platform
newData's AI engine is powered by Rapidminer, a world leader in Data Science and AI platforms. Our talented data science team leverages this platform to build and deploy powerful predictive models, segmentations, and simulations. We customize every solution without the expense.
Competitive Prices
AI is all about efficiency, which is why our solutions aim to perform tasks faster and with fewer errors. This fundamental concept translates to how we work, too, in that our solutions cost less to develop and result in higher quality at lower prices for our customers. When we save money, so do you.
AI Platform
Enterprise AI technology for small to mid-sized businesses
Scale
Our AI platform can be deployed at the enterprise level but is also scalable to be effective for a smaller company. Our passion is helping small to mid-sized businesses with limited data experience, technological resources, and personnel achieve their business missions through data science innovations. We take the hassle and complexity out of AI so that you can focus on what your business does best.
Accuracy and Precision
The intersection of technology and seasoned data science professionals ensures that our clients get the most accurate and precise modeling solutions available. It also ensures that those solutions are customized to their specific business problems.
Automation and Speed
A key benefit of Rapidminer's AI platform is the increased speed and reduced costs that come along with process automation. Whether your goal is reducing the amount of manual data entry and error checking in structured or unstructured text, or the efficient deployment of models and the measurement of their impact, newData's data science team can leverage the full automation capabilities of our AI platform.
AI Platform
newData's AI engine is powered by Rapidminer, a world leader in Data Science and AI platforms. Our talented data science team leverages this platform to build and deploy powerful predictive models, segmentations, and simulations. We customize every solution without the expense.
Competitive Prices
AI is all about efficiency, which is why our solutions aim to perform tasks faster and with fewer errors. This fundamental concept translates to how we work, too, in that our solutions cost less to develop and result in higher quality at lower prices for our customers. When we save money, so do you.
DREAM is our tech integration process
Click on a letter to find out more
Dashboard success is built by working effectively with people, not just machines.
We believe in collaborate engatement
We begin the DREAM process by gaining an understanding of your business challenges and identifying new opportunities. We show how your desired outcomes can be harnessed through data, technology, and analytics with enthusiasm about quantifying the impact of closing performance gaps and growing your share of the pie.
Once we have a general understanding of your data, we continue our DREAM process by developing a business intelligence roadmap that includes best practices in design, dashboard development, analytics, implementation, and measurement. Our dashboards are easy to navigate, so they get used, and actionable, so they impact your bottom line.
While we are creating your dashboard, our development process is highly collaborative — we call it Iterative Dashboard Development (IDD). This means there are never any surprises, because each dashboard is customized to fit your business like a glove.
After every engagement, we stay connected with you to ensure your business continues to reap the benefits of increased revenue, lowered costs, and mitigated risks.
We design and implement business intelligence dashboards that help businesses tell a story with their data and take action on the insights
DREAM is our tech integration process
Click on a letter to find out more
Machine learning success is built by working effectively with people, not just machines.
We believe in collaborative engagement
We begin the DREAM process by gaining an understanding of your business challenges and identifying new opportunities. We show how your desired outcomes can be harnessed through data, technology, and analytics with enthusiasm about quantifying the impact of closing performance gaps and growing your share of the pie.
Once we have a general understanding of your data, we continue our DREAM process by developing a business intelligence roadmap that includes best practices in design, dashboard development, analytics, implementation, and measurement. Our dashboards are easy to navigate, so they get used, and actionable, so they impact your bottom line.
While we are creating your dashboard, our development process is highly collaborative — we call it Iterative Dashboard Development (IDD). This means there are never any surprises, because each dashboard is customized to fit your business like a glove.
After every engagement, we stay connected with you to ensure your business continues to reap the benefits of increased revenue, lowered costs, and mitigated risks.
Modeling use cases
Fraud detection
Risk managers decrease losses by predicting fraudulent transactions using powerful anomaly detection algorithms and synthetic data to establish baseline performance.
Customer acquisition
Marketing managers at banks increase revenue by predicting profitable customer segments likely to respond to specific digital and traditional marketing solicitations.
Customer retention
Marketing and operations managers minimize lost revenue by proactively implementing retention strategies for accounts likely to churn.
Customer behavior
Marketing managers increase customer engagement by personalizing messages to behaviorally-based segments while risk managers ensure that the default risk of customers in these segments do not exceed a pre-defined or dynamic threshold.
Cross-selling
Marketing managers increase existing account profitability by identifying the “next-best action” based on the customer’s expectations, propensities, and likely behavior.
Collections
Collection managers increase debt collected by predicting which delinquent loans are mostly likely to be recovered.
Better cash/liquidity planning
Credit managers track past usage patterns of customers at ATMs, branches, and online locations to predict the relevance of new liquidity instruments that may better serve their needs.
Marketing optimization
The marketing team can utilize past multi-channel campaigns to inform how the overall budget can be allocated and to target customers with right message at the right time.
Customer Lifetime Value (LTV)
A customer's lifetime value provides information about how long to expect the customer to stay with the bank and how much income the bank is likely to generate. Predictive models can move customers' profitability and retention by identifying the attributes of the best customers.
Application screening
New account specialists process huge volumes of applications, without excluding important variables, without delays or errors, and without growing tired -- all with regularity and steadiness.
Disease diagnosis and prediction
Medical professionals improve the healthy outcome of patients by decreasing the misdiagnoses of diseases and increasing the accuracy of prognoses
Operating room bottlenecks
Clinicians combine real-time data with information about event scheduling to improve workflows, the timeliness and relevance of important notifications, and the handoff of a patient from one area to the next.
Symptoms and health concerns
Chatbots improve health outcomes of patients by listening to symptoms and health concerns and then guiding patients to the correct care based on their diagnosis.
Over-prescription of antibiotics to babies
Nurses apply the results of a predictive model using a risk calculator that better targets newborns who are at the highest risk for sepsis without exposing those at low risk to antibiotics.
Earlier cancer detection
Oncologists improve patient survival rates by improving the quality of screenings, diagnostic tests, and blood work.
Research-enhanced insights
Radiologists improve patient survival rates by augmenting their diagnoses with the latest cancer research through analyzing scanned images and comparing them to findings.
Care transitions after surgeries
Hospital administrators reduced lengths of stay for patients receiving total hip and knee replacements by predicting which patients required inpatient rehabilitation and which would successfully recover at home.
Machine Learning (ML) is no longer a "nice to have" for manufacturers. To remain competitive, ML is a neccessity for manufacturers to optimize factory workflows, forecast demand for products and components, minimize product defects, and reduce production and supply chain disruptions.
Demand forecasting
Forecast demand for manufactured products or components to allocate resources most profitably.
Maintenance planning
Proactively anticipate maintenance needs by predicting unscheduled workflow disruptions.
Product design
Reduce warranty claims by improving product design based on historical service patterns.
Customer insights
Segment customers based on product features, support logs, pricing, and competitive offerings.
Environment, health, and safety (EHS) risk
Reduce EHS risk by predicting the drivers of non-compliance.
We’re excited to add use cases for many industries.
Please be patient as we grow!
We’re excited to add use cases for many industries.
Please be patient as we grow!
Using past data to predict what is likely to happen in the future, identify actionable insights, and intervene to reduce costs, increase revenue, and mitigate risks.
Don’t wait. The time will never be just right.
Mark Twain
