Becoming Information-Driven Begins with Pragmatic AI

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Written by guest blogger, David Schubmehl, IDC Research Director, Cognitive/Artificial

Intelligence Systems.  Sponsored by Sinequa.

Over the last several years, I’ve spoken to many organizations that have all asked the same question: How can we most effectively make use of all of the research, documents, email, customer records and other information that our employees have collected over the years, especially those that are now retiring? In the past, organizations had corporate libraries and corporate librarians whose job it was to help collect, organize, and disseminate information to employees and staff when and where they needed it. That department and positions are long gone from most organizations today. Why have they gone? The rate of data and documents (including research papers, contracts, and even emails) has exploded, making this task impossible. But let’s be honest: even before today’s information explosion, no classification system could ever keep up with the fast pace of change in the economy. No one could have foreseen today’s most important questions, in content categories that did not exist until today. And with the baby boomers retiring at an ever-increasing rate, an urgent question must be asked: How do organizations get the most value from the vast amounts of information and knowledge that they’ve accumulated over decades?

IDC has identified the characteristics of organizations that are able to extract more value out of the information and the data available to them. Leader organizations make use of information access and analysis technologies to facilitate information access, retrieval, location, discovery, and sharing among their employees and other stakeholders. These insight leaders are characterized by:

  • Strategic use of information extracted from both content and data assets
  • Efficient access to unified and efficient access to information
  • Effective query capabilities (including dashboards)
  • Effective sharing and reuse of information among employees and other stakeholders
  • Access to subject matter experts and to the accumulated expertise of the organization
  • Effective leverage of relationships between information from different content and data sources

So how can artificial intelligence (AI) and machine learning affect information access and retrieval? The types of questions that are best answered by AI-enabled information access and retrieval tools are those that require input from many different data sources and often aren’t simple yes/no answers. In many cases, these types of questions rely on semantic reasoning where AI makes connections across an aggregated corpus of data and uses reasoning strategies to surface insights about entities and relationships. This is often done by building a broad-based searchable information index covering structured, unstructured, and semi-structured data across a range of topics (commonly called a knowledge base) and then using a knowledge graph that supports the AI based reasoning.

AI-enabled search systems facilitate the discovery, use, and informed collaboration during analysis and decision making. These technologies use information curation, machine learning, information retrieval, knowledge graphs, relevancy training, anomaly detection, and numerous other components to help workers answer questions, predict future events, surface unseen relationships and trends, provide recommendations, and take actions to fix issues.

Content analytics, natural language processing, and entity and relationship extraction are key components in dealing with enterprise information. According to IDC’s Global DataSphere model developed in 2018, of the 29 ZB of data creation, 88% is unstructured content that needs the aforementioned technologies to understand and extract the value from it. In addition, most of this content is stored in dozens, if not hundreds of individual silos, so repository connectors and content aggregation capabilities are also highly desired.

AI and machine learning provide actionable insights and can enable intelligent automation and decision making. Key technology and process considerations include:

  • Gleaning insights from unstructured data and helping to “connect the dots” between previously unrelated data points
  • Presenting actionable information in context to surface insights, inform decisions, and elevate productivity with an easy-to-use application
  • Utilizing information handling technologies that can be used in large scale deployments in complex, heterogeneous, and data-sensitive environments
  • Enriching content automatically and at scale
  • Improving relevancy continuously over time, based on user actions driven by machine learning
  • Improving understanding by intelligently analyzing unstructured content

IDC believes that the future for AI-based information access and retrieval systems is very bright, because the use of AI and machine learning coupled with next-generation content analysis technologies enable search systems to empower knowledge workers with the right information at the right time.

The bottom line is this: enabled by machine learning–based automation, there will be a massive change in the way data and content is managed and analyzed to provide advisory services and support or automate decision making across the enterprise. Using information-driven technologies and processes, the scope of knowledge work, advisory services, and decisions that will benefit from automation will expand exponentially based on intelligent AI-driven systems like those that Sinequa is offering.

For more information on using AI to be an information leader, I invite you to read the IDC Infographic, Become Information Driven, sponsored by Sinequa at https://www.sinequa.com/become-information-driven-sinequa/

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Surfing the Cognitive Search Wave (as a Leader) Again

The Forrester™ Wave: Cognitive Search, Q2 2019
Sinequa has again been named a leader in “The Forrester™ Wave: Cognitive Search, Q2 2019.” The report is available for download here.

For global enterprises with complex use cases, Sinequa stands out as the right platform, according to the latest Forrester™ Wave1.

Let’s take a closer look and unpack some of the underlying details….

“Sinequa augments intelligence en masse […] to help organizations become ‘information driven’ by augmenting the intelligence of every employee.”

This statement astutely captures Sinequa’s view that it’s not about the data, the software, or analytics, it’s about the people. This perspective lies at the heart of our tagline, Become Information-Driven, which implies that organizations should leverage modern technology to power solutions that help individual knowledge workers accomplish their goals in order for the entire organization to perform at peak levels and outcompete in their market.

“[Sinequa] accomplishes this by surfacing knowledge, uncovering insights, and connecting experts via its cognitive search technology.”

These are indeed critical capabilities that should transcend the current (or future) state of the customer’s IT environment. As Sinequa-powered solutions can (and should!) be deployed wherever the relevant content and data resides – whether it be on-premise, in private or public clouds, or as a hybrid model – Sinequa customers can choose the deployment model that best aligns with their strategy and security policies, particularly when it comes to hosting sensitive data in the cloud.

“Sinequa expertly balances using its own NLU technology in combination with the latest open source ML technology.”

At its core, the Sinequa platform employs technology that automates the interpretation of meaning and applies structure to unstructured content. It intelligently combines deep natural language processing, rich semantic analysis, advanced entity extraction, and machine learning technology. This combination distills meaning from unstructured content and removes the noise, producing a clean and enriched index that consistently provides relevant information in context. In recent years, Machine Learning technology has been expertly woven into the platform to enhance understanding of complex data through experience instead of (or along with) codified business rules. Cohesively integrating these technologies into the Sinequa platform has effectively produced a production-grade machine learning platform for any enterprise.

“[Sinequa] has significant industry expertise in and offers solutions for life sciences, financial services, and manufacturing.”

This is no accident. With over a decade of experience, Sinequa understands the attributes of our most successful customers and realizes that they thrive with Sinequa because:

  • They are geographically-distributed and knowledge-centric
  • They have ambitious business goals and sophisticated IT environments
  • They routinely collaborate internally across geographies and across lines of business to drive decisions
  • They depend on highly diverse, high value content and data in different languages to drive their business forward
  • They either work with Systems Integrators for project execution or have their own in-house resources with a dedicated focus on systems integration

At Sinequa, we realize that a large share of our customers match these criteria and occupy the verticals pointed out by Forrester – i.e. life sciences, financial services, and manufacturing. After all, this is where Sinequa’s core competencies and unique capabilities can make the biggest impact.


1 Forrester Research, Inc., “The Forrester Wave™: Cognitive Search, Q2 2019” by Mike Gualtieri, with Srividya Sridharan and Elizabeth Hoberman.

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Sinequa Featured in IDC Technology Spotlight Dedicated to Financial Services Organizations

ScreenHunter_1549 Jan. 16 16.48With increased regulatory pressures, data silo proliferation and cognitive drain on analysts, AI-powered platforms become a key enabler to extract insights from data.

Today, we announced that Sinequa is featured in a new IDC Technology Spotlight report: Financial Services Organizations: Extracting Powerful Insights with AI-Powered Platforms. The report, written by Steven D’Alfonso, research director, IDC Financial Insights, and David Schubmehl, research director, Cognitive/AI Systems, highlights the importance of AI-powered platforms in their ability to extract insights from data as well as the need for financial services organizations (FSOs) to improve their capabilities to derive insights from the data they possess.

According to the report, collecting and maintaining increased amounts of data related to their clients and portfolios can provide major opportunities to improve the customer experience and increase revenue while reducing risk. But at the same time, too much data can be a cognitive drain on analysts and knowledge workers. This increasing need to collect data from multiple applications requires FSO stakeholders to organize and provision their data in ways that allow analysts to extract meaningful insights. AI can help FSOs mature from being data-driven to being information-driven.

“Over the years, Sinequa has continued to expand its footprint within leading financial institutions such as Credit Agricole, DZ Bank, LCL, Navy Federal Credit Union, and U.S. Bank as our platform enables them to tackle the challenges highlighted in this report,” said Scott Parker, director of product marketing at Sinequa. “By offering a broad-based AI-powered platform including search, content analytics, semantic understanding and auto categorization technologies, Sinequa provides relevant insights to users in their work environments, while supporting a range of machine learning algorithms and capabilities to improve findability and relevance, allowing FSOs to access the information they need when they need it.”

With the demand for AI technologies that enable intelligent analytics increasing every year, IDC estimates that “by 2022 spending on AI technologies will grow to over $8 billion, up from $2 billion in 2017.” Sinequa has in the past offered a flexible information collection, access and analysis architecture and now provides cognitive capabilities, such as machine learning, natural language processing, improved relevance and better decision support, while offering intuitive user and data interaction capabilities.

To learn more, click here or on the banner below to sign up for the webinar.

idc-finance-webinar

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Sinequa Wins the 2018 KM Promise Award

In addition to the awards Sinequa has collected this year – KMWorld Trend-Setting Products, Datanami Readers’ Choice Award, and Bio-IT 2018 Best in Show, just to name a few – we are excited to return from KMWorld / Enterprise Search & Discovery 2018 with yet another trophy.

On Wednesday, November 7th, at the KMWorld conference in Washington D.C., we participated in the Awards Ceremony for the finalists of the KM World Promise and the KM World Reality awards. The KM Promise Award is given to a company that implements and integrates knowledge management practices into business processes and works with clients to ensure they reach their goals. The award recipient provides innovative technology that breaks through the hype to help customers gain insights, collaborate and compete in a mobile and global business environment. The KM Reality Award recognizes an organization in which knowledge management is a positive reality, not just rhetoric. The award recipient has demonstrated leadership in the implementation of knowledge management practices and processes, realizing measurable business benefits.

We are very honored to have received the 2018 KM Promise Award. The other finalists in this category included ASG Technologies, BP Logix, DocStar, Nuxeo, Unifi Software and Workgrid Software. Laurent Fanichet, our VP of Marketing, accepted the award on behalf of Sinequa, followed by Jill Harris, Delta Airlines Sr. Communications Coordinator, who picked up the KM World Reality Award.

award

“2018 is a fantastic year for Sinequa. Leader for the third time in a row in the Gartner Magic Quadrant for Insight Engines, we are experiencing triple-digit growth as we continue to expand in North America with the opening of an office in San Francisco, among other major milestones. Winning the KM Promise Award is great validation of the value of our approach and the completeness of our solution. This reaffirms our commitment to offer our customers the most advanced Cognitive Search & Analytics platform to provide them with relevant and contextual insights to make better decisions, drive innovation and achieve greater operational efficiencies,“ said Fanichet.

booth

In addition to winning the award, we had a very successful show at KMWorld! It was a pleasure to meet with our customers and partners at our brand new lit-up booth and see new faces at the very well-attended keynote presentation from Scott Parker, Sinequa Director of Product Marketing, titled “Becoming an Information-Driven Organization.”

keynote

We look forward to returning to DC next year and adding more trophies to our “honors” shelf in the New York office! In the meantime, we are rounding up 2018 with a few activities – a KMWorld-hosted roundtable webinar on Cognitive Search and Analytics in Action (November 27) and exhibiting sponsorships at the AI World Conference in Boston (December 3-5) and the Forrester Data Strategy & Insights Forum in Orlando (December 4-5).

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Sinequa Snags Three Key Industry Award Wins in September

Sinequa Industry Recognition - September 2018

We’re off to a busy September here at Sinequa! We’re excited and humbled to have received a few different awards for our Cognitive Search & Analytics Platform and company as a whole this month. Sinequa recognition has included the following awards from leading industry publications:

KMWorld Trend-Setting Products 2018

KMWorld’s 2018 list of Trend-Setting Products features not only emerging software directed toward human-like functionality but also more traditional offerings impressively refined. It encompasses AI, machine learning, cognitive computing and the Internet of Things, as well as enterprise content management, collaboration, text analytics, compliance and customer service. Read more.

DBTA’s Cool Companies in Cognitive Computing for 2018

DBTA and Big Data Quarterly presented the 2018 list of Cool Companies in Cognitive Computing to help increase understanding about the important area of information technology and how it is being leveraged in solutions and platforms to provide business advantages. Read more.

Datanami Readers’ Choice Award Winner

Sinequa won the Readers’ Choice – Best Big Data Product or Technology: Machine Learning category.

The Datanami Readers’ and Editors’ Choice Awards are determined through a nomination and voting process with input from the global big data community, as well as selections from the Datanami editors, to highlight key trends, shine a spotlight on technological breakthroughs and capture a critical cross-section of the state of the industry. Read more.

Looking forward to continuing the momentum for the rest of the year!

For more information on Sinequa’s cognitive search and analytics platform visit: https://www.sinequa.com/insight-platform-2/

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