Approach

Our goal is to provide streamlined solutions driven by cutting-edge AI technology that lead the industry in precision, accuracy, and ease-of-use. The success behind all of our solutions lies in our expert team and the diverse set of tools and methodologies they bring to the table relative to other AI companies.

Working with Dynam.AI:

Our processes are flexible enough to serve companies at any stage of their AI journey. From initial discovery through solution delivery, we tailor our solutions to the needs of our customers – something other AI companies providing off-the-shelf tools will never do.

Discovery

In-depth analysis of your business
data and use case

Delivery of a report detailing a
roadmap for implementing AI
and expected milestones

Proof-of-concept

Initiate a pilot project on a specific use case

Establish proof of concept and viability
of enterprise implementation

Demonstrate tangible business value
and scalable ROI for your use-case

Deployment

We help you build your enterprise-wide
data pipeline

Full implementation, including software
engineering and interface design

Algorithm optimization, and tailoring to
achieve max performance

In a global survey of more than 3,000 executives, approximately 75% of participants said they believe AI holds the key to new business opportunities for their companies. Nearly 85% of respondents believe AI will give them a distinct competitive advantage in business. Yet, despite this excitement over AI’s potential, only one in five companies currently uses AI, and an astounding 60% of companies lack a strategy altogether.

Sloan Review, MIT

Case Study

Reducing Hospital Re-admission Rate with Explainable AI

Hospitals around the United States struggle with preventing re-admits – when a patient has to return to the hospital within 30 days of being discharged for the same medical condition. Re-admits are extremely costly for medical insurance carriers and patients. In fact, Medicare charges hospitals a 3% penalty for re-admits, and in 2015, hospitals across the United States were fined $420 million in re-admission penalties.

In 2017, a major university hospital group looked to Dynam.AI data scientists to help them identify the variables causing re-admits and to predict the likelihood of a patient’s re-admission risk during the initial visiting.

Solution

We took into consideration various data sets, such as demographics or cause of the original visit to create a risk score for patients. Staff assignment, performance, and work schedules were also built into the model. Additional data input variables included the total number of returning patients, total visits per year, age, ailments, triage code, facility, marital status, sex, type of accident, primary payer code, and various other factors when determining the best AI technology solution. In total, over 62,000 patient visit records were included. Our solution was built with full data transparency to elevate the visibility of key factors causing re-admission and enable real-time decision making.

Results

Our solution achieved 90% prediction accuracy for patient re-admits. Armed with this predictability and visibility into factors closely related to re-admits, the hospitals were able to make changes that resulted in a 30% reduction in re-admission and savings of $20 million in fines for the university hospital group.

Differentiators

As leaders in time series data, our algorithms and techniques allow us to deliver unrivaled AI technology providing not only superior prediction accuracy but also the ability to fully explain why those predictions are made. Our algorithms and models are a highly specialized blend of techniques and approaches adopted from neuroscience, physics, machine learning, dynamical systems theory, and control theory. Combined with our client-focused approach, this allows us to deliver unmatched performance.

Time series data techniques provide a 360-degree view allowing businesses to grasp past changes, actively monitor what’s happening in the present, and predict how things may occur in the future.

Deep neural nets use more complex variables and represent a more accurate description of systems than other deep nets.

Counter to the typical black-box AI solutions, our explainable AI allows users to understand the AI’s logic, increasing confidence in the recommendations produced.

Our approach to neural nets enables our algorithms to exhibit constant self-improvement and superior agility to adjust to ever changing real-world dynamics.

We combine the best AI techniques available from across the industry with our own proprietary algorithms and methodologies, ensuring the most advanced solutions for our customers.

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