The Problem

PingThings was a startup looking to build a real-time platform to leverage machine-learning for physical systems on the electric utility grid and high-value industrial assets such as GSU transformers and step-down transformers. They wanted an analytics platform to track sensor data, focusing on storing and manipulating time-series data and modeling complex relationships between synchrophasors’​ high-resolution signals.

Sector Energy

Vertical Analytics

Model LightGBM/XGBoost

Case Study

Blue Orange helped build the first production prototype of PingThings’ PredictiveGrid. The PredictiveGrid is an Advanced Sensor Analytics Platform (ASAP) architected to ingest, store, access, visualize, analyze, and train machine learning and deep learning algorithms with sensor data measuring the grid with nanosecond temporal resolution.

Initial predictive problems addressed:

  • Rapid post-event analysis and reporting
  • Sensor data cleaning and management
  • Fault detection, prediction, and localization
  • Anomaly identification, classification, and prediction
  • Failure signature identification


Sales Optimization in Private Equity

Phase 4: Improve Portfolio Company Performance

The Challenge

A leading Private Equity and Venture Capital firm, with over $20B under management, requested an end-to-end data audit of their deal platform. They were looking to evolve the platform to make a scalable and unified sourcing tool with consistent architecture and infrastructure. They wanted an independent third-party to assess the technical decisions made to date in the development.

The firm needed help integrating 4 newly acquired CRM/ERP companies. Each acquired company had its own databases, in its own format. A lack of visibility into the sales process of these siloed data systems hindered coordination…


The Challenge:

In marketing and sales, new ways to reach out to customers and prospects come out every year. It’s exciting and frustrating at the same time. With limited resources, how do you make strategic choices about which marketing methods, media, and technologies to use? You can guess and hope for the best. Or you can adopt a data-driven methodology.

Extermax, a game company, wanted greater predictability in their customer acquisition process. Without that in place, meeting their growth and financial goals would become much more difficult. Blue Orange helped them get answers with a data-driven methodology. …


The Problem

Uiba offers Machine Learning for Organizational Management to medium and large-sized organizations. This platform enables their clients to hire, allocate, and develop their workforce in a manner designed to maximize productivity, minimize cost, and achieve optimal efficiency. Blue Orange developed and designed the first version of its platform.

Sector Tech

Vertical Talent Analytics

Model SVM/Random Forest

Case Study

Uiba required a Machine Learning solution for Organizational Management. We built an internal talent discovery platform to help companies identify, allocate, and develop their workforce. Blue Orange designed the tool to:

  1. Index all organizational capabilities by team, role, and employee.
  2. Optimize talent distribution to maximize productivity.
  3. Only hire externally when required. Focus on discovering internal talent.

Bidirectional Encoder Representations from Transformers, otherwise known as BERT; is a training model that has drastically improved the efficiency and effect of NLP models. Now that Google has made BERT models open source it allows for the improvement of NLP models across all industries. In the article, we take a look at how BERT is making NLP into one of the most powerful and useful AI solutions in today’s world.

Applying BERT models to Search

Google’s search engine is world-renowned for its ability to present relevant content and they have made this natural language processing program open source to the world.

The ability of a…


Intro: Machine learning in the solar energy industry

The high availability of data in the energy sector makes it a great environment for machine learning and data science solutions. Power grids, energy networks, consumers, smart homes, and appliances are only a few examples of rich data sources. They enable energy providers to better understand their role in the energy ecosystem and to optimize their operational performance.

Moreover, specific sectors are seeing a spike in innovative solutions made possible by the increased data availability. In solar energy, disruptive business models and custom applications are at the forefront of innovation. …


In business, the needle in a haystack problem is a constant challenge. Recommendation Engines are here to help tackle that challenege.

In e-commerce and retail, you offer hundreds or thousands of products. Which is the right product for your customers?

In sales and marketing, you have a large number of prospects in your pipeline. Yet, you only have so many hours in the day. So, you face the challenge of deciding where precisely to focus your effort.

There is a specialized technology powered by AI and Big Data, which makes these challenges much easier to manage, recommendation engines.

What are recommender systems?

In its…


Your data knows you best, let it find your dream home.

The real-estate industry sits on tons of data that goes unused every year. In this article, we discuss how advanced technologies are helping real estate investors, brokers, and companies utilize the mass amount of information within the industry to help people find their dream homes.

In 2017, a Field Actions Science Reports article addresses the impact of AI, machine learning, and predictive analytics on the real estate sector:

“The practice of AI-powered Urban Analytics is taking off within the real estate industry. Data science and algorithmic logic are close…


The Smart Cities of today are powered by advanced technologies that are constantly reshaping urban areas. AI and IoT are becoming increasingly integral to how the world operates. Cloud-based services, the Internet of Things, analytics platforms, and many AI tools are changing the way citizens interact with and move within their environment.

These modern technologies, as outlined by Blue Orange Digital, a top-ranked AI consulting and development agency in NYC, enable applications ranging from waste management to food supply optimization and healthcare digitization. In the process, they are disrupting entire industries and creating new business opportunities and applications.

Among all…


IoT technologies increase the accessibility to patient data, enable real-time decision making, and offer ease and efficiency through automation.

IoT-powered software solutions for the healthcare sector are shifting the focus from digitalization to intelligence. IoT technologies increase the accessibility to patient data, enable real-time decision making, and offer huge potential for automation. Combined with predictive modelling and advanced software and hardware capabilities, IoT devices are helping healthcare facilities address some of their most pressing pain points.

Here are four examples of innovative, IoT-powered solutions that are demonstrating the impact of technological progress upon the entire healthcare sector.

1. Real-time asset management

Asset management is…

Blue Orange Digital

Blue Orange is a data science consulting and machine learning development firm. Founded by engineers, we love passionate technologists and data analysts.

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