Neural Search

The next generation of Search Relevance

The evolution of Enterprise Search relevance

Today, individual employees still spend at least 400 hours each year searching for information, resulting in millions of dollars in operational costs and lost business opportunities. While enterprise search engines have reduced that effort with the advent of NLP technologies applied to the text found in documents, we are still in the early stages of AI-driven information discovery. The next stage of this evolution will come from applying deep learning models to enable machines to understand language intent and present more relevant information to employees, known as Natural Language Understanding (NLU). With NLU, the shift from employees finding information to information finding employees will be accelerated, further unlocking productivity and innovation.

Guide to Natural Language Processing (NLP)

Natural language processing is the science behind machine comprehension. If you’re new to the concept or looking for an overview of what it is and how it’s used, then this guide is for you.

Sinequa Neural Search - the next generation of search relevance

Sinequa Neural Search

Sinequa’s Neural Search provides the most sophisticated engine for discovering enterprise information assets available on the market today.

By combining state-of-the-art deep learning language models with the best NLP and statistical techniques, employees and customers spend less time searching for information and more time developing insights to drive decisions and solutions.

Sinequa’s Neural Search improves the enterprise search experience with the following key features:

  • Multiple deep learning models to collect information based on advanced machine learning that uses deep neural networks (DNNs) for natural language understanding (NLU).
  • Unified retrieval combines keyword-based (statistical) and language-based (neural) for better search results.
  • Performance optimization to keep data-processing costs manageable and information retrieval latency low. We leverage Microsoft Azure instances and Nvidia’s newest Tensor GPUs for inference testing and benchmarking.

Benefits of using Sinequa Neural Search include

Improved relevance

Improved relevance

Sinequa’s Neural Search augments the performance of the existing best-in-class statistical search so that you can expect better relevance for any existing use case. Neural Search also has the potential to perform well in situations where statistical search hasn’t been used for lack of matching words.

Information in context

Information in context

Neural Search shows the most relevant passages for greater contextual insights rather than just matching words.

Answers to natural language questions

Answers to natural language questions

Using deep learning, Neural Search extracts the most relevant answers from existing content, shortening the time-to-insights.

Easy to deploy

Easy to deploy

Neural Search comes ready to go out-of-the-box. All four models are pre-trained to perform well on enterprise content and do not require training on your dataset, now or in the future. Our models incorporate years of research and knowledge and are optimized for the best relevance to enterprise content. Harness the power of natural language AI without the need to build and maintain training datasets, or curate content.

Fast and efficient

Fast and efficient

Normally language models are big and unwieldy...which means costly infrastructure or expensive hosting bills. Sinequa’s Neural Search has been designed for performance from the very beginning to scale to enterprise levels and for cost-effective deployment on large datasets, including millions of documents.

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Nasa
Pfizer
Franklin templeton Investment
Total Energies
Societe Generale

The next leap forward in Search Relevance

What the analysts say

"Sinequa significantly differentiates itself through its use of deep learning (artificial neural networks), and how it uniquely applies multiple deep learning models to provide more accurate search results. "

Alan Pelz-Sharpe - Founder

Deep Analysis

Discover what Sinequa can do for your business

Sinequa’s Search Cloud brings organizations of all sizes the most complete enterprise search ever. Schedule a personalized demo to show how Sinequa can benefit your organization.
Related content
Replay Inform Online 2022 - Sinequa Neural Search

Replay Inform Online 2022 - Sinequa Neural Search

Watch Jeff Evernham's demo to understand what neural search is, what are the use cases that could benefit of neural search, and why neural search is different.

Guide to Natural Language Processing

Guide to Natural Language Processing

Natural language processing is the science behind machine comprehension. It’s the study of how to translate the spoken word into something a machine programmed with ones and zeros can understand. But it’s far more than just knowing words.

Intelligent Analytics Capabilities

Intelligent Analytics Capabilities

Natural Language Processing (NLP) and Machine Learning power the advanced features of Sinequa's Intelligent search platform. After more than 25 years of NLP research, we are experts at making sense of each piece of text, whatever the native language.

Frequently Asked Questions

What is neural search?
What is BERT?
What use cases do we expect Neural Search to benefit?
How is Sinequa’s Neural Search different?
Does Neural Search replace Sinequa’s existing statistical search?
Is Neural Search processing-intensive?
Will Neural Search be included in the standard license ?
Is it available now?
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