The ‘Naturally Intelligent’ Phenomenon
Saffron unifies and connects millions of data points from disparate sources. The Natural Intelligence Platform of Saffron does not need a specific framework for the data to be presented; it can ingest information from any form—public, private, transactional, open source, textual, social media content, blogs, and news articles. Unlike other systems that use rule-based models, the platform makes sense from all available data—structured or unstructured— using cognitive methodologies. After ingesting the data, Saffron stores these connections, their counts, and context in an associative memory base, enabling rapid knowledge exploitation. The platform processes the same through a reasoning layer built of algorithms to rapidly analyze and identify patterns to help people quickly make sense of events and support decision-making.
“Organizations can be quickly overwhelmed by big data. Traditional software and artificial intelligence platforms use models and rules to make sense of data, but when you don’t know what’s in the data, you quickly find that these systems are rigid and not adapted to the new world of the Internet of Things,“says Gayle. “Saffron doesn’t require that you know much about the data or what’s in it. We begin analysis without models or rules. The raw data is the real model. As context changes, we adapt, identifying patterns in the data not previously known or understood.
The Natural Intelligence Platform’s analytic reasoning methods support decision making in real time with tools such as network analysis, entity personalization, automatic classification and scoring, anticipatory analytics, temporal convergence, and episodic patterns. Patterns are presented and analyzed through a seamless visual interface to the user, enabling organizations to easily identify actionable insights, manage risks, and adapt their strategies to achieve their goals of personalized customer experiences, revenue growth, and cost efficiency.
With the advent of social media, customer interaction has increased on a large scale and data generation has also taken a natural hike. Customers expect companies to know who they are, how to engage with them, and how to exceed their expectations quickly. Social Media platforms and the Internet of Things are drastically increasing the amount of data available for analysis. This trend represents an opportunity for businesses to capture novel insights on the use of their products and services. “Yet, even though companies are getting better and better at capturing this data, most still struggle to unify it and make it meaningful for their organization,” Gayle adds.
Saffron’s web services architecture easily integrates with various data sources and legacy. The technology performs independently—or in coherence with existing apps—to create more intelligence from data, thus focusing on helping companies anticipate the future. “Our technology does not require constant curation as it naturally identifies connections in the data along with the context and frequency of these connections. This natural representation of knowledge, coupled with Saffron’s cognitive distance capability, provides companies intelligence from all types of data in real-time,” adds Gayle.
We envision a world empowered by cognitive technology. From the smallest companies to Fortune 500 enterprises
Mitigating Client’s Jeopardy
The solution offered by Saffron Technology in the cognitive computing space has no limitations with regard to implementations in various industry verticals. Manufacturing, Defense, Energy, and Healthcare are a few of the industries where the Natural Intelligence platform has been leveraged. Saffron’s Natural Intelligence Platform also has the potential to transform healthcare research and practice. Physicians can use the platform to assist in diagnosing and treating patients by having it analyze large amounts of unstructured and structured text together in order to recognize patterns too complex for humans to detect reliably.
A good example is in the areas of cardiology, where distinguishing between two types of heart disease—restrictive cardiomyopathy and constrictive pericarditis—continues to pose a challenge even for top cardiologists, who provide correct diagnoses of these diseases only 76 percent of the time. Dr. Partho Sengupta, Director of Cardiac Ultrasound Research and Associate Professor of Medicine in Cardiology at The Mount Sinai Hospital, needed a way to accurately identify disease patterns resulting from echocardiograms in order to improve diagnostics and save more lives.
Saffron, without the use of restrictive models or extensive data training, improved the diagnosis accuracy by 90 percent, outperforming top physicians (76 percent) and state-of-the-art decision trees (54 percent). Their work with Dr. Sengupta continues forward.
Journey so far and the road ahead
When Dr. Manuel Aparicio and James Fleming conceptualized the idea of building Saffron Technology in 1999, their prior experiences at IBM naturally came to use. The duo delved deep inside analytical engineering to develop and bring cognitive computing to everyone. Now, under the leadership of Gayle Sheppard, the company continues to follow the same principle and to help organizations use all the information available to make better, more accurate decisions. “We envision a world where end users and decision makers are empowered with cognitive technology— from the smallest companies to Fortune 500 enterprises. Our mission is to enable people to make wiser decisions in their lives and for their businesses by using Saffron’s Natural Intelligence platform,” says Gayle.
With funds coming in from strategic investors, Gayle continues to steer the company toward niche channels of Big Data. The captain is confident on her path: “While sailing, the conditions and situations you face are varied and complex. You assume tremendous responsibility when you take a sailboat offshore and there are a variety of challenges, presented by various data inputs. Sailing is as much about riskmanagement and decision-making as it is about seamanship. Likewise, big data promises to help us navigate forward by leveraging past experience to understand the present and anticipate the future. The goal is obvious, but hard to do: make the best, most accurate decisions to manage risks and seize opportunities."
The Natural Intelligence Platform
The Natural Intelligence Platform uses knowledge from prior experiences to anticipate and suggest future outcomes. The platform unifies disparate data sources and identifies people, places, and things and their connections in real time. Next, the knowledge representation layer in the platform uses similarity-based reasoning to anticipate what will happen next—without models or pre-determined data frameworks—to help companies with real-time anticipatory thinking.
It recognizes every chunk of data that could be in any form—structured, unstructured, data present outside and inside the company’s infrastructure. It learns all data in real time and constantly connects and counts the dots, unlike traditional systems. The platform correlates information from data by linking people, places, products, and things and speeds up the automaticity of association of information to simply help enterprises “Come with data and go with intelligence.”