Sinequa Recognized as a Leader in the Gartner 2015 Magic Quadrant for Enterprise Search

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As of 19 August 2015, Gartner, Inc. recognized Sinequa as a leader in the recently released Magic Quadrant for Enterprise Search. Leaders are recognized for their “completeness of vision” as well as their “ability to execute”.

Sinequa moved up into the “Leaders” quadrant from our position amongst the “Visionaries” in the 2014 Magic Quadrant. We incorporated significant technical innovation in its product over the last year, and gained a number of high profile customers in the USA and Europe. Our customers showed great creativity in implementing impressive use cases with strong ROI. Using Sinequa as a unified information access platform, they were able to increase their agility to the point of coming up with Search Based Applications (SBA) within a few weeks. In the process, they gained greatly in standing with their user community and are considered real “business partners” for them. 

According to Gartner, “leaders have the highest combined measures of ability to execute and completeness of vision. They have the most comprehensive and scalable product portfolios. They have a proven track record of established market presence and financial performance. For vision, they are perceived in the industry as thought leaders, and have well-articulated plans for enhancing recovery capabilities, improving ease of deployment and administration, and increasing their scalability and product breadth.”

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For more details, please download Gartner’s 2015 “Magic Quadrant for Enterprise Search” here.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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How Can Big Data Search and Content Analytics Help Revolutionizing Pharmaceutical R&D?

How can Big Data Search and Content Analytics help revolutionizing Pharmaceutical R&D?A recent report from Accenture estimates that the U.S. healthcare could potentially generate $300 billion in annual healthcare cost savings through efficiencies and quality improvements offered by Big Data and Analytics. The good news is that we have seen over the past couple of years an increased adoption from leading biotech, pharmaceutical companies tapping into this real-world data with very positive results and very tangible ROI. The big data opportunity in pharmaceutical R&D is real, and the rewards will be great for companies that succeed.

So the question is as a leading life sciences company, you must be wondering: “what are the potential benefits for my organization?” How do you drive new insights and greater value from Big Data and Content Analytics?

Well, imagine a future where you could do the following:

  • Speed up submission of New Drug Applications to dramatically reduce costs for new drugs development
  • Make educated decision to continue or stop drug trials based on all clinical trial data available
  • Provide researchers a unified access across the entire organization to all structured and unstructured data from both internal and external wide variety of sources
  • Drive innovation, accelerate research and shorten Drug Time-to-Market
  • Foster cooperation in R&D while respecting information governance and security
  • Catalyze drug repositioning

What if we are telling you, the future is already here so step into the future!

Click here

By Laurent Fanichet, VP Marketing  - Sinequa

 

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What is Natural Language Processing (NLP)? Why Should You Care About It?!

Linguistic and deep semantic analysis cope with the biggest challenge of Big Data analytics: textual data or human generated data. Semantic analysis helps in understanding your questions as well as the meaning of texts beyond simple keyword matches. It also helps to cluster information via business-relevant filters to dramatically improve discovery of relevant information.

What would you use NLP for?

To get relevant information, all relevant information, nothing but relevant information… if you want to leverage all your enterprise data, you will definitely need it!

I can hear you say: “But isn’t NLP just text extraction, word separation, language identification? … many search engines do that, why would I need Sinequa?”

Because we are the experts when it comes to NLP! And here are the main four reasons that make Sinequa’s Linguistic Analytics stand out:

  • Automatic concept and entities extraction from linguistic patterns and an out-of-the-box facets navigation
  • Strong text mining capability with “Part of Speech tagging”
  • “Semantic correlations”, for example co-occurrence of concepts within a single phrase.
  • Easy integration of “enterprise knowledge”: dictionaries, ontologies, etc.

All of these features help you extract value from textual data, such as projects reports, clinical trial reports, publications, patent filings, and emails. In many companies this data contains a wealth of information that has not been “codified” in sheer figures. In fact, it often contains the reasons why the figures are what they are.

And you want this extraction to be fast and easy, such that your employees find relevant information in their work environment without having to know where it comes from and in what format it is in.

If you are in a pharma company looking for information on a particular drug, you want to use your brand name but get results on all synonyms, the active molecule in that drug, on other drugs with the same active molecule, on diseases treated with these drugs, on experts working on these drugs and molecules – all without having to specify any synonyms or relations in your request for information.

In a globalized world, you will want the system to “speak your language”. I.e. you need a multilingual system. Sinequa offers NLP in 20 different languages, including “difficult” ones like Chinese, Japanese, Korean or Arabic.

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What About Having 140+ Connectors To All Your Enterprise Data Sources?

An Enterprise Search platform only deserves its name if it connects easily to all or at least most your data sources. If you need access to a data source, you want to have it now, not in 3 months’ time.  Or rather: you need to have it now.

Sinequa offers more than 140 indexing connectors ready for use, developed by our R&D team who can thus control quality and performance. The connectors are non-intrusive, meaning they do not alter in any way the contents and data to be indexed – and they “remember” access rights to all data. Moreover, Sinequa provides a generic connector as a template for developing any additional connectors you may need.

The Sinequa R&D team has continued to develop new connectors to data sources, now at a total of 140 (including PTC Windchill, Mongo DB, Scality, Office 365, box…), as well as to refine language analysis in the 20 languages covered by Sinequa, specifically in Asian languages including Chinese, Japanese and Korean.

You want to go into the cloud? We are already waiting for you.

The Sinequa platform integrates with the major cloud offerings, in particular with Amazon Web Services (AWS) such that customers can benefit from an “elastic” computing facility hosted on the Amazon cloud, and from certain services specific to AWS. The “elasticity” of Sinequa on AWS lets customers instantly scale computing resources to their requirements at each moment in time, be it for the indexing of a large new data source or when adding a large number of users spread across geographical regions.

An Out-Of-the-Box Connectivity to the most widespread structured and unstructured data sources facilitates and accelerates the integration of the Sinequa Big Data & Search platform with your IT landscape. This makes Sinequa projects most often an order of magnitude shorter than the big IT projects (ERP, CRM, BI, etc.) that IT departments have painfully grown used to in the past.

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Have You Heard About SBA “AppStores”?

You are overwhelmed with business data coming from diverse and multiple data sources and with demands from various user populations to make use of this data? In that case you should look at how to construct your own App Store!

You may be wondering “How on earth am I going to that?”

But our customers achieved it! They built their own SBAs on the top of our advanced search & analytics platform. And now, they have created an “SBA factory” serving all kinds of business needs.

Sinequa ES is designed for high performance content analytics across functions and industries, it offers a powerful platform to create search-based applications (SBA) with hitherto unimaginable speed. This allows them to create Apps for any operational, individual and data need.

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Our unique content analytics, including Natural Language Processing, produce a “rich” index, with information added on top of the original sources: meta-information, concepts and relationships between contents, etc. Only such a rich index can serve as a platform for an abounding and ever-growing set of Search Based Applications (SBA): Its richness ensures that even the SBAs you haven’t thought of as yet will find the information they need to serve their users in the index. If you need to delve into the original data sources, Apps become too difficult to construct.

Our customer AstraZeneca’s vision is to have Search nourish their next generation of business intelligence software and help create new applications. They have created a particularly innovative “App Store”.

Curious now to know more about these Apps and see how they have been deployed?

Click here to request further information

 

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