“Our mission is to create ‘apps’ that make the Internet of Things think like a human brain”: App Orchid Inc

IT departments are currently plagued by gaps between data collection, insights and action. They constantly find themselves hand-holding non-technical teams like marketing, sales and HR. And often times, they have a limited number of information sources at their disposal. That is, if they haven’t empowered their company with cognitive technologies.

Many business leaders already understand that cognitive computing is going to be a major disrupter. Whether you choose to embrace it to your advantage or not probably going to determine the outcome of how your business performs and survives going forward.

Today, there are more data multipliers than ever before including humans, machines, and business processes—and the volume of structured and unstructured data (social media posts, documents, emails, images, videos, audio recordings, customer feedback, manuals, industry reports etc.) is growing exponentially. Until recently, businesses were blind to the valuable insights hidden in unstructured content. Then businesses started implementing cognitive solutions through their IT departments, and trends, patterns, insights, and relationships became readily apparent. There are many ways cognitive computing is empowering IT departments to boost performance across teams and improve their bottom line.

The increasing demand of AI and Cognitive Computing came to be the root cause of App Orchid’s genesis. App Orchid Inc. is a Silicon Valley based software developer specializing in the science of Artificial Intelligence and Cognitive Computing.

Billions of intelligent endpoints that make up the Internet of Things have created exponential growth in the amount of analytical data that corporations and other organizations are attempting to make sense of in order to improve efficiency, manage risk, and provide superior customer/client/patient service. Where once businesses only had to respond to operational data in structured format (databases), the Internet of Everything provides us with an opportunity to break the barriers of these data silos, and integrate this structured data with unstructured data in found on the internet, social media, news and weather. Organizations also benefit by tapping into their own “tribal knowledge” that exists in the unstructured form of reports, emails, evaluations, presentations, and observations.

App Orchid applies artificial intelligence and natural language processing to extract and blend structured data from the Internet of Things and operational databases, with unstructured, free-flowing data from Tribal Knowledge and the Internet of Everything. It then uses Big Data based in-memory technology to perform deep learning to identify patterns, risks and opportunities previously impossible with traditional analytical tools. Its Natural Language and/or gamified UX makes retrieving accurate answers as simple as typing a question in Google.

An outline of the company

App Orchid was founded in 2013 by Krishna Kumar, a repeat entrepreneur with experience in founding similar successful enterprise companies. Based in Redwood city, the company has grown exponentially with multiple customers in healthcare, insurance and energy verticals. Within a short span of 24 months, the company has expanded to over 50 employees at an annual growth rate of over 500% to about 10M in annual revenues.

The world of AI is fast coming to us. Large Scale problems in various industries like energy and healthcare were still largely untapped. For example, the founding team at App Orchid believes that on an average several metric tonnes of CO2 could be capped with smart application of AI technologies between the supply, demand and transmission hubs. Similarly, complex drug discovery challenges could be addressed by contextually combining the tribal knowledge of technicians, doctors and pharmacologists. These and other such problems only need us to use common sense applications of the sophisticated advancements seen in mobility, networking and cloud in general.

In conversation with the dignitary: Krishna Kumar, Founder/ CEO

Could you elucidate about the present market scenario?

AI and Machine Learning apps are taking the industry by storm. While the consumer markets have responded and adapted well to these advancements, the enterprise ecosystem is still struggling with data issues and viable use cases that justify multi-million dollar investments in these projects.

What is your company’s current possie?

App Orchid’s product suite primarily caters to dealing with vast amounts of unstructured [like Word documents, PowerPoints, emails etc.], structured and IoT [Internet of Things] data. Currently, App Orchid has over 15 enterprise customers implementing over 25 use cases with application of technologies from SAP, IBM amongst others. For theses groundbreaking projects, the company has won multiple accolades such as SAP HANA Innovation award, Gartner cool Vendor for 2016, Top 15 companies to watch amongst others. Using cutting edge data science, artificial intelligence and natural language interfaces, analysts can now develop powerful business apps and solutions with minimum IT oversight and governance, thereby deploying applications in production within weeks.

How are you idiosyncratic? 

App Orchid’s product stack primarily deals with vast amounts of unstructured and structured data. App Orchid takes an “App based” approach allowing organizations to take smaller bites, while being able to test and try out advanced AI concepts without overwhelming their operational systems. Such a non-invasive approach allows enterprises to “test-drive” their business functions and check the viability of applying revolutionary digital technologies against their landscape.

A rapid prototyping approach enables them to quickly assess what works and what doesn’t, thereby providing them with data points to quickly production enable viable ideas while seamlessly dismantling ideas that don’t work. App Orchid is the only company that provides a very rich template of prebuilt business recipes that enable for rapid test driving and deployment of AI applications. Using a unique approach towards AI based on a technology called the “semantic web”, the technology is automatically capable of performing knowledge discovery, i.e. discovering relationships between the data points, knowledge acquisition, i.e. acquire the knowledge and automatically load the data into its data structures and finally knowledge curation, i.e. convert the data into predefined app templates. This unique approach dramatically reduces the time to market and the cost of deploying the application in a production setting.

Stumbling blocks for the industry

Data is not locked in silos anymore. Enterprises are learning to embrace external data feeds like social media, web blogs and competitive intelligence to stay ahead of the game. Digitally savvy institutions like Uber and Amazon are threatening established and proven industry best practices like retail and transportation and in many cases making them obsolete.

Industries like insurance and energy are realizing that next generation ideas like micro underwriting are threatening their foundations and very existence. New energy sources like Renewables, though energy efficient, are very complex to integrate into their current energy networks. Mandates like the Paris climate accord are forcing these organizations to embrace energy conservation and green energy objectives, when their electric grids are not capable of handling the volatile supply of these resources.
In areas like personalized medicine, new generation drugs that are genetically engineered to attack cancerous tumors cannot be easily market ready due to the complexity and regulatory challenges associated with the clinical trials of these drug pipelines.

In summary, with advancements in mobility, internet and networking, several trillions of billions of man-years of collective wisdom has now made it to the digital universe, but is largely untapped. Enterprises that don’t cash in on this gold-mine of intellectual treasure trove will lend themselves obsolete in short order.

App Orchid- Industry savior

The Power of App Orchid Apps for the Utility Enterprise

Today’s electric grid is a myriad of smart meters, communicating controls, power line sensors, and thousands of other intelligent endpoints. All these devices are creating an exponential growth in the amount of analytical data that utilities are attempting to make sense of to improve grid reliability, increase efficiency and provide superior customer service. But the thousands of terabytes of data locked in these structured database systems represent only a fraction of the utility’s collective intelligence. The rest is trapped in unstructured data that can be found in reports, emails, white papers, PowerPoints, field assessments, customer interactions, equipment manuals, and perhaps even more important, experiential observations from utility personnel at all levels that it refers to as “tribal knowledge.”

Imagine if we somehow could access and assimilate all these information sources: structured data in operational database stores, unstructured tribal knowledge, and external data from the internet and social media, to create an intelligent virtual repository that could be queried using simple apps that can be cross pollinated to provide exceptional insight.

The Power of App Orchid Apps for the Insurance Enterprise

For decades, the insurance industry has led the world in predictive analysis and risk assessment. And today, with the treasure trove of big data available, insurance companies have the opportunity to take this discipline to a whole new level of accuracy and consistency.

The actuarial models that were once driven solely by large internal and external databases can now be fueled with tremendous quantities of unstructured data from social media, online research and news, weather and traffic reports, real-time securities feeds, and other valuable information sources as well as by “tribal knowledge” such as internal reports, policies and regulations, presentations, emails, memos, and evaluations. In fact, it is estimated that 90% of global data has been created in the past two years, and 80% of that data is unstructured. Now add the Internet of Things — computers, smart phones and wearables, GPS enabled devices, transportation telematics, sensors, energy controls, and medical devices.

Creating Knowledge from the Internet of Things, Structured Data, and Medical Tribal Knowledge

The explosive growth of wearable and surgically implanted sensors, combined with the ever increasing digitization of medical records has created massive growth in the data available to the healthcare and medical research industries. Wearable clinical devices are expected to surpass $6 billion in sales by 2019, and more and more people are sporting watches and smart phones that record heartbeat, and other vital signs throughout the day.

The result is an explosion of data points that reside in thousands of databases around the world. Within these data stores is a treasure trove of knowledge that may hold the answers to many of the most challenging questions facing modern medicine. However, all this data that resides in the traditional structured format of a database schema is dwarfed by the unstructured data that exists within the tribal knowledge of healthcare professionals – the observations, diagnoses, prognoses, family histories, reports, published articles, and clinical studies that have been the traditional lifeblood of modern medical practice. Imagine the exponential increase in the value of the knowledge base we could create if we could blend this structured data with unstructured tribal knowledge on the fly.

A succinct apropos the products and services of the company 

App Orchids solution ranges from Energy Management, Insurance Risk Assessment and Underwriting and finally Clinical trials for personalized medicine and targeted therapies.

Energy and Natural Resource Management:

App Orchid’s AI technology helps to integrate complex wind and solar energy profiles into the electric grid. Using high performance machine learning, the AI apps can identify sections of the electric grid that are prone to failure and remedy these inconsistencies before they cripple the grid.

Actuarial Analysis [Risk Management] for Insurance:

App Orchid can help combine unstructured documents like compliance, regulations, market rules, regional mandates with risk analytics for superior risk profiling and evaluation.

Catastrophe Risk and Damage Analysis for Utilities and Insurance: Incorporate historical weather patterns, news, research reports, and social media, into calculations of risk from potential catastrophes to price coverage or determine prudent levels of reinsurance.

Targeted Risk Analysis (Single view of customers): With the wealth of individual information available on people and organizations, App Orchid makes it possible to apply AI and cognitive computing principles to provide risk profiles targeted down to an individual. For example, a Facebook profile of a mountain climbing enthusiast would indicate a propensity for risk taking that might warrant a different profile than a golfer. Claims Processing By unifying unstructured data across historical claims, App Orchid solutions make it possible to establish ground rules (or quantitative metrics) across fuzzy baselines that were previously not possible.

Targeted therapies in drug discoveries:

By combining complex genomic data with electronic medical records, unstructured diagnosis reports and toxicology reports, the App Orchid AI bots can predict drug efficacies, toxicity and viability across several conditions. Such powerful tools can dramatically help life science companies formulate personalized therapies thereby increasing the predictability of a success in a drug pipeline.

Top clients of the firm and related case studies to highlight the story

Energinet’s [Energy], American Water [Water conservation], Fortune 20 Oil and GasCompany and Fortune 100 Insurance. All of 3 focus industries are tracking equally well.

Case studies

A Unified Customer view for the Largest Water Company in North America: A fortune 500 Water company was having challenges with understanding their customer behavior, especially as it related to water consumption and high bills. Customerre presentatives had a tough time educating the customers with these issues often causing frustration and poor customer reviews. Using AI, App Orchid’ solutions combined the internet of things from smart meters, customer interaction records, billing and other similar data feeds to provide the customer representatives with a single pane of glass view across the complete customer ecosystem.

Fortune 100 Insurance Company: Underwriting and Risk Profiling. Actuarial models were driven solely by large internal and predefined external databases. Tremendous quantities of unstructured data from social media, online research and news, weather and traffic reports, real-time securities feeds, and other valuable information sources as well as by “tribal knowledge” such as internal reports, policies and regulations, presentations, emails, memos, and evaluations just did not make it to the internal risk assessment procedures. Due to this, large gaps were noticed in the risk profiles and the company lost a lot of business to the competition through price gaps and incoherent risk assessments. Using the App Orchid technology, a single pane of glass view was provided to integrate risk profiles, customer demographics and historical claims thereby integrating the multiple moving parts in the underwriting process.

A Portent of Things to Come

The firm plans to extend its platform using next generation compute technologies like GPU to gain deeper insights in healthcare, insurance and energy. For example, App Orchid is currently working on using AI to analyse medical images and mammograms that will help in early stage cancer detection and diagnosis. Though, these kinds of research are already underway in several institutions, the AI platform is unique because it combines lots of unstructured and other third party contextual data sources to influence its training algorithms.

Embrace the prodigy persona

Krishna Kumar is an entrepreneur, innovator, visionary and architect with proven expertise in taking a concept to a market-leading industry recognized commercial product. Under his leadership, AppOrchid has emerged out of stealth mode with 3 products that are set to revolutionize Cognitive Computing, Machine Learning and the “Internet of Everything” markets.

With 3 locations - Silicon Valley, Israel and India, the company is perfectly positioned to tap the best talent necessary for this exciting venture.

"We harness the power of artificial intelligence, machine learning, and natural language processing to extract and blend structured data from the Internet of Things and operational databases."