& Machine Learning
Our team will guide you to find meaningful and actionable analytics from your data.
Forecast the future by using techniques such as predictive modeling, predictive pattern matching, multivariate stats, forecasting, and regression analysis.
Identify the recommended actions based on the forecast, using techniques such as neural networks, graph analytics, heuristics rule engine, complex event processing, operations research, and optimization.
Build models that are capable of understanding and interpreting unstructured data streams, such as free text and audio. Then, perform the appropriate set of actions based on the interpreted data.
Analysis & Strategy
Working with SMEs (subject matter experts) and stakeholders to identify the problem to be solved, define the hypothesis, and visualize what the final model would look like (classifier or predictor).
Identify the data sources that are best suited to solve the problem or validate the hypothesis. Build the right pipelines to get access to the data.
Determine the criteria for success and be specific as we determine the baseline model.
Work with SMEs to determine the baseline features that are most correlated to the output that you want to predict.
Evaluate various algorithms to identify the model that best meets or supersedes the evaluation criteria.
To further validate or improve the model, test the models in production and with newer data that was not used in the model building.
Cut your costs and reduce human error by using robust ML models. Uncover your operational capabilities by leveraging machine learning algorithms and models. Some examples include:
- Classification of customer churn
- Automated customer interactions
- Fraud prediction
- Tailored user experience
AI-driven virtual assistants and chatbots can gather valuable marketing data for your business and enhance your users’ experience. Not to mention, they can have hundreds of conversations simultaneously. Enhance your technological capabilities by embracing the future of customer service.
Will your patient cancel their future appointments? Can late payments be handled without third-party intervention? Will your sales prospect take action? Our data science can use models to help predict the future and help you to drive innovation one step at a time.
Manage uncertainty and risk by embracing the new level of security and performance with custom machine learning algorithms.
- Portfolio management
- Claims management
- Fraud detection
- Stock market forecasting
- Algorithmic trading
Drive employee retention rates. Leverage algorithm to attract, screen, engage and hire the best talent.
- Applicant monitoring & assessment
- Improved recruitment
- Reduced human biases
- Fake CV handling
Acquire new customers. Build, analyze, and optimize your marketing performance one step at a time.
- Customer behavior analysis
- Personalized marketing campaigns
- User-driven content generation
- Buying patterns recognition
Simplify lead generation and create smarter sales pipelines with thoroughly qualified prospects and data-driven approach.
- Prospect data analysis
- Enhanced sales forecasting
- Real-time marketing feedback
- Automated routine
“Newfire became not just an extension, but a part of our team. They’re truly the first vendor I’ve worked with in 27 years of the healthcare industry who are almost completely aligned with what we’re trying to do as a company.”
“The world is changing quickly and so is Buoy Health. Newfire is a partner who really understands our product and became part of our team. This has been the best engagement of my career.”
“Newfire has proven to be a true partner who is committed to client success. They bring both technical expertise and business understanding.”
“Partnering with Newfire has allowed my team to gain momentum without having to provide daily management. They actively find ways to add value, even in a complex environment where directive can change. I’m very impressed with their technical expertise and ability to help us scale as an organization.”
“In today’s dynamic business world, we require partners that we trust and can respond to our needs. The team at Newfire has consistently shown a deep-rooted commitment to our shared success and values.”
“Our partnership with Newfire involves more than simply meeting our talent needs. Newfire provides valuable expertise and is the advisor we need to accelerate solving some of healthcare’s toughest challenges. I trust our team at Newfire and am more confident in our ability to produce high-quality output.”
“From the moment we engaged with Newfire, we were immediately impressed with the caliber of their executive team. They gave us good direction and starting the collaboration was very straightforward. As we started interviewing developers, it became clear that Newfire prioritizes talent above all else.”
“Having turned over responsibility for developing clinical tools to Newfire, I’ve been freed to pay more attention to the member experience work over the past few years. And with the arrival of Newfire’s member experience team, I look forward to being able to spend much more time on strategic concerns.”
- How do AI services work?
Newfire’s AI services allow you to quickly configure and deploy business solutions using pre-built AI/ML models, in real-time. Using industry-specific chunks of data, AI services make it simple to scale without investing in IT infrastructure, hosting environments, and senior in-house developers.
- What is AIaaS?
AIaaS (Artificial Intelligence as a Service) is an offering with out-of-the-box AI solutions. It’s easy to set up a platform, and there’s no need to further invest in infrastructure or in-house developers. AIaaS can be scaled up or down according to your goals and business requirements.
- What is MLaaS?
MLaaS (Machine Learning as a Service) is a blend of ML tools as a feature of cloud technologies. It offers tools for data processing, visualization, natural language processing, predictive analytics, and deep learning. The main benefit of MLaaS solutions is that there’s no need to build infrastructure or hire in-house data scientists for model training and data processing stages. You pay for exact predictions, not for the IT infrastructure.
- Can AI improve healthcare?
AI has many implications in healthcare, but we believe that it’s some of its best applications are for:
- Early disease detection
- Help with treatment plans
- Data-backed decision making
- Associated care
- Remote health monitoring
- Easier access to medical services
- What is the role of ML in healthcare?
Machine learning (ML) is a set of practices that automates and improves the way computers learn from data. For healthcare, ML allows glimpsing at comprehensive data analytics, predictive analysis results, and real-time patient data processing. Because of this, ML increases the efficiency of new treatment options, which may have been unavailable before due to lack of data analytics and unification.