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Healthcare.
Reliability.
Rails Reactor.

30+
30+ early stage &
VC-backed Startups
90%
90% of our projects
incorporate ML/AI
100
100 Engineers  
& experts
$1B+
Enterprise clients with
over $1B+ in revenue
We specialize in solving complex problems arising in fast-evolving healthcare and pharma sectors. We align our teams to solve all kinds of technical and digital challenges and deliver business value.

Our Expertise

Schmit–
Thompson
Protocols

Clinical
Trials

Patients
Health
Records

EMR
EHR

HL7
Protocols

mHealth

Medical
Call Centers

ADD


Adverse

Drug
Events

Safety
Document
Distribution

HIPAA

TeleHealth

ADD


Video
voice
text

Our Experience

Medical
Personnel
Onboarding

Caregiver Application


Reporting

Systems

Patient

Portal

Mobile
Solution

Portfolio Management
System

drug
research

Triage

Call Centers

Dispatch

Modules

Medical Personnel

Mobile Solutions

eWallet


for
Insurance

Medical Research
Analytics

Our Clients

■   Insurance
     Companies

■   Clinical
     Research

■   Healthcare
     Startups

■   Pharma
     Companies

■   Health
     Research

■   Hospital
     Chains

How we stand out

Reliability & Insurance

Working in a high-paced IT landscape can be difficult for healthcare companies. Every healthcare software project has some fraction of uncertainty due to the numerous requirements, compliances, and complex internal processes which must be considered. These put healthcare companies at risk of being behind schedule or having an inappropriate solution delivered when working with a software vendor.
Being aware of these healthcare software challenges and having year-over-year success in building sophisticated solutions for healthcare leaders, including Partners Healthcare and IQVIA, Rails Reactor insures and ensures reliable deliverability. We ensure that projects meet the schedule and requirements, and clients are insured to be billed only when they accept the delivery.
Healthcare software must be reliable.

Software vendors too.
Rails Reactor is.

Our Projects

The System provides medical researchers with a simple user Interface to the data repository of well organized clinical histories, which can be queried and summarized both for biomedical research and clinical care.  This provides efficient access to aggregated data for performing a variety of tasks, such as  assisting in diagnosis or treatment, identifying patterns in treatment, selecting subjects for clinical trials, and monitoring  participants in clinical trials.
Technology
  • .NET
  • MS SQL Server
  • JavaScript
  • SASS
  • Dragula
  • AngularJS
  • Flow
  • Redux
  • Peg.js
The Insight Research Portal is a web-based healthcare application supporting over 10,000 current users in researching new cures. Developed for the research community (including investigators, departmental research managers, unit chiefs, and administrators), such users review, monitor and manage their research portfolios.
Technology
  • .NET Core
  • ASP.NET Core
  • Entity Framework
  • Azure Service Fabric
  • Microservices
  • Docker
  • JavaScript
  • SASS
  • React
  • Redux
  • MS SQL Server
Our easy-to-use solution lets medical researchers query data using natural English language either as text or voice and converts it into a structured SQL request. We also developed a rich User Interface and chatbot which communicates with  users to supplement the NLP parser. The speech system is designed to continuously refine its ability to ‘hear’ and understand a wide variety of accents and automatically adjusts to a particular  customer’s requests.
Technology
  • .NET
  • Python
  • C++
  • PyTorch
  • Flask
  • Peg.js
  • StarSpace
  • Numpy
  • WaveNet
  • Audacity
  • JavaScript
  • MS SQL Server
  • SASS
  • Dragula
  • AngularJS
  • Flow
  • Redux
Machine Learning
  • Deep Recurrent Neural Networks
  • Sequence to Sequence Architecture
  • Speech Recognition
  • Noise Reduction
  • Dependency Parser
  • Word Lemmatization and Tokenization
  • Reinforcement Learning
  • Entity Recognition
One of the challenges faced by caregivers visiting patient’s homes is identifying and recording medical/pharmaceutical information in an accurate and efficient way. There are two options which rely on image recognition functionality and may allow a caregiver to shorten the time of their visit. One relies on OCR and lets a caregiver  record pharmaceutical information by reading drug labels. The other option relies on identifying a drug by its color, shape, and engraving. To ensure accuracy, the results are presented to the caregiver for final approval.
Technology
  • Python
  • Kubernetes
  • Tornado
  • Apache Spark & Luigi
  • SSD
Machine Learning
  • PyTorch
  • STN-OCR
  • YOLO v3

    Our Technologies

    We are highly skilled across a wide variety of technologies and can leverage our diverse and broad skill sets to achieve tailored software products.  Our engineers are expert technologists focused on client delivery.
    CLOUD
    • Heroku
    • EC2
    • Digital Ocean
    • Google Cloud
      platform
    • AWS  S3
    • Azure
    Database
    • MS SQL Server
    • PostgreSQL
    • Aerospike
    • Redis
    • Cassandra
    • Elasticsearch
    • MongoDB
    • MySQL
    • Oracle
    WEB
    • Java
    • Scala
    • .NET
    • PHP
    • Ruby
    • Python
    • React
    • Angular JS

    We’ll make your product smarter, with Artificial Intelligence & Machine Learning

    Artificial Intelligence and Machine Learning techniques are bringing a paradigm shift to healthcare, thanks to the increased availability of data and the rapid progress of analytics techniques. AI can be applied to various types of healthcare data (structured and unstructured).
    Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning method, as well as natural language processing for unstructured data.

    Computer Vision & Image Recognition

    Natural Language Processing

    Chat Bots

    Data Mining

    Voice Technology

    Big and Small Data Processing

    Humanizing Technology

    with User Experience

    Investing in a properly structured UX process at the development stage helps identify the factors that can lead to project failure, and also reduces the likelihood of rework.
    Our commitment to developing the best applications begins well before a single line of code is written.
    Planning, testing, and an overall commitment to creating a product that addresses its users’ real needs lead to greater profitability over time and a clearer path to growing your business.

    Our Engagement Models

    Project-based

    You tell us your problem and challenge. We form a team (PM, BA, designers, engineers, QAs etc.) and they work till the issue is solved.

    Team Augmentation

    You have your team in place, but need a few additional people with specific skill set? We have them. Tell us whom you need and we’ll bring the right people.

    Digital Transformation

    “90% of CEOs believe that digital economy will impact their industry, but less than 15% are executing on a digital strategy”
    MIT Sloan and Capgemini
    As healthcare becomes more user/patient-oriented and continues to exist in a highly regulated environment, clients are seeking to offer user/patients more choice, and greater access and control to healthcare information. Digital transformation in healthcare means points of care can digitize paperwork and upgrade their legacy systems to enhance quality and time-efficiency, reduce costs and substantially decrease human error.

    The key to adopting an effective digital transformation is of course seeking to solve the right kinds of challenges in the first place, but then also working with the right  technologies — technologies which meet the specific demands of the project.

    Healthcare AI & ML

    AI is “a core, transformative way by which we are rethinking how we are doing everything”
    Google CEO Sundar Pichai
    Artificial Intelligence and Machine Learning techniques are bringing a paradigm shift to healthcare, thanks to the increased availability of data and the rapid progress of analytics techniques. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning method, as well as natural language processing for unstructured data. Machine Learning and NLP algorithms we use:

    • Support Vector Machine
    • Neural Networks
    • Logistic Regression
    • Discriminant Analysis
    • Random Forest
    • Linear Regression
    • Native Bayes
    • Nearest Neighbor
    • Decision Tree
    • Hidden Markov

    Voice Technology & Chatbots

    “You should message a business just the way you would message a friend”
    Facebook CEO Mark Zuckerberg
    Interactive phone calls and chat bots  enable hospitals, health practices, and insurance companies to reach out automatically to their entire patient population or a select group instead of staff members’ having to make individual phone calls. For patients, the greatest benefit of voice and chat bot technology is its potential to promote better health practices. We work with clients to provide a “human” experience and are able to provide effective outreach to patients outside of the hospitals or doctor’s offices.

    Our Healthcare Experience with technology:
    • Virtual Triage Assistant
    • Virtual Dispatch Assistant
    • Patient’s Identification by voice
    • Voice component to the cohort builder

    Big Data to Small Data

    “The clinical enterprise is the realm of small data. That’s because small data are directly related to patient care”
    Thomas Prewitt Jr., M.D.,
    Director of the Healthcare Delivery Institute at HORNE LLP
    Small data resides in hospitals, clinics, and communities. This data is stored in electronic medical records (EMR), paper charts, and pharmacy systems. Fitness centers, restaurants, churches, and other venues are also potential sources of small data. (And increasingly, consumer devices.)

    We use small data towards  specific insights. To answer predetermined questions,  data-analysis expertise has been ‘baked’ into  selected slices of data to be shown, into the parameters put in place to scope down the volume of data, and into the carefully chosen method of visually representing the data. As a result, it can be understood, interpreted, and acted upon without much mathematical or statistical expertise.

    Our Clients

    Connect With Us
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