Category: Enterprise search & search technology (Page 9 of 61)

IBM released an open-sourced part of the IBM Deep Search Experience in a new toolkit, Deep Search for Scientific Discovery (DS4SD), for scientific research and businesses with the goal of spurring on the rate of scientific discovery.

To help achieve this goal, we’re now publicly releasing a key component of the Deep Search Experience, our automatic document conversion service. It allows users to upload documents in an interactive fashion to inspect a document’s conversion quality. DS4SD has a simple drag-and-drop interface, making it very easy for non-experts to use. We’re also releasing deepsearch-toolkit, a Python package, where users can programmatically upload and convert documents in bulk.

Deep Search uses AI to collect, convert, curate, and ultimately search huge document collections for information that is too specific for common search tools to handle. It collects data from public, private, structured, and unstructured sources and leverages state-of-the-art AI methods to convert PDF documents into easily decipherable JSON format with a uniform schema that is ideal for today’s data scientists. It then applies dedicated natural language processing and computer vision machine-learning algorithms on these documents and ultimately creates searchable knowledge graphs.

https://research.ibm.com/blog/deep-search-toolkit

Tellius announced a partnership with Databricks to give joint customers the ability to run Tellius natural language search queries and automated insights directly on the Databricks Lakehouse Platform, powered by Delta Lake, without the need to move any data.

With Tellius, organizations can search and analyze their data to identify what is happening with natural language queries, understand why metrics are changing via AI-powered Insights, and determine next best actions with deep insights and AutoML. Connecting to Delta Lake on Databricks only takes a few clicks, and then users can perform a natural language search of their unaggregated structured and unstructured data to answer their own questions. They can drill down to get granular insights, leverage single-click AI analysis to uncover trends, key drivers, and anomalies in their data, and create predictive models via AutoML in Tellius. Answers and insights can be utilized to write back to source applications to operationalize insights. Faster data collaboration helps democratize data access across analytics teams with less worrying about performance or IT maintenance.

https://www.tellius.com/tellius-and-databricks-partner-to-deliver-ai-powered-decision-intelligence-for-the-data-lakehouse/

Sinequa, a Search Cloud provider, strengthened its integration with Microsoft by enabling its customers to easily procure Sinequa’s Search Cloud platform directly from the Azure Marketplace using private offers. Sinequa is now available on the Azure Marketplace for all Microsoft Azure Consumption Commitment (MACC) customers. With this new private offer, customers can now fulfill license subscriptions for Sinequa under their existing MACC, allowing them to decrement pre-committed Azure spend. Sinequa license and Sinequa workloads on Azure will be counted 100 percent toward the MACC.

Sinequa and Microsoft customers can benefit from co-sell engagements to bring Search Cloud solutions to their Azure tenant. Sinequa also works with Microsoft’s Cloud Solution Provider (CSP) program to deliver world-class search to Global 2000 customers.

Sinequa’s Search Cloud Platform, optimized for Azure, is an enterprise search platform that enables innovative organizations to ingest enterprise data sources, transform that data into searchable information, and obtain precise insights to natural language queries.

https://azuremarketplace.microsoft.com/en-us/marketplace/apps/sinequa.sinequa_macc_enabled