Corporate Wide Search

Organizations are increasingly becoming insight-driven. Together with the rapid development of AI technologies like machine learning and NLP, the demand for AI-enabled search and analytics solutions will become more prevalent. As we begin 2019, our Managing Director, Kamran Khan, shares some of the most notable observations around these capabilities.

In his years as a search engine programmer and architect, our Innovation Lead, Paul Nelson, has come across lots of business-critical as well as creative uses for search engines. Here’s a roundup of 10 prevalent search enterprise use cases he has helped organizations explore and implement over the years.

By implementing enterprise data lakes, companies have started to see multiple benefits. But to gain valuable insights from their data lakes, effective solutions are needed to help users find the right answers and relevant datasets from the massive amounts of data. Watch our Innovation Lead discuss how Natural Language Processing and search can help companies unlock the full value of the data lake.

As the Google Search Appliance (GSA) is approaching its end-of-life, Google has announced its cloud replacement: Google Cloud Search. A Google partner with significant enterprise search expertise, we have been working with Google on the roll-out to learn about Cloud Search features, perform deployments for clients, and provide feedback for future evolution. Read about our engineer's first-hand review of Google Cloud Search.

In this blog post, we discuss how Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques can be used to create knowledge graphs, which can then power chatbots, question/answer systems, and search engines to deliver holistic enterprise knowledge and improve business outcomes.

Solr vs. Elasticsearch has been discussed so frequently on our blog and within the enterprise search community. But as traditional enterprise search has evolved into what Gartner calls “Insight Engines,” we revisited this topic to provide the latest observations, including cloud deployments, integration with big data analytics, and cognitive search capabilities. Read on to find out the key criteria to consider if you’re weighing between Solr and Elasticsearch in 2018.

Developed by our team at Accenture Applied Intelligence and our partner Microsoft, this demo leverages Aspire Content Processing and Azure Cognitive Services to enhance unstructured data preparation, enabling advanced, cognitive search functionalities in Azure.

New innovations have been rapidly accelerated by big data analytics, artificial intelligence, cognitive computing, and machine learning. Interestingly, a common theme emerged: search is the stepping stone and enabler of these technologies. Read this blog to see how search opens new doors for insight discovery across all enterprise functions.

The Google Search Appliance (GSA) has reached its end-of-life. If you haven't started your transition planning, now is the time to do so. In this blog, our GSA expert discusses the top 5 considerations when replacing your GSA with an open source alternative, such as Elasticsearch or Solr. The discussion also touches on cloud-based GSA replacement options that can support scalability and cost-savings.

A critical part of a data lake implementation is having effective mechanisms for the data to be copied from different repositories to the data lake. In this blog, our architect discusses potential challenges, best practices, and common methods for data acquisition as well as how to select the most appropriate implementation approaches for your data lake use cases.