Content discoverability is one of the most powerful features that symbolizes how responsive and engaging a communication platform is.
We all know that content search across randomly located and a gigantic collection of heterogeneous data is incredibly time-consuming. Needless to say, this leads to a bad user experience which stifles creativity. In the age of AI, this makes us ask one question – can content search be automated?
To the rescue, AI-enabled Microsoft search and impending integrations are hopefully going to take user search experience to next level very soon.
Azure Cognitive Search
For simplifying the search process for its users, Microsoft brings Azure Cognitive Search service by incorporating AI capabilities for your platform. Azure Cognitive Search service uses natural language processing for easy identification of content across functional areas of vision, language, and speech. Using this service, you can customize your app based on a selected criterion i.e., the type of input data you are working with.
Integrating Cognitive Services with MS Teams
So, if you use Microsoft Teams as your virtual collaboration platform, you can now enhance its usability with AI-driven enrichment using Azure Cognitive Search in the following ways:
- You can make varied forms of undifferentiated content such as text, images, voice, and application files searchable in web, devices, and enterprise applications.
- You can automate indexing and create user-defined search index. Additionally, you can simply query construction using search APIs, and implement search-related features such as faceted navigation, filters (including geo-spatial search), synonym mapping, autocomplete, and relevance tuning.
- Similar to commercial search engines, MS Teams can be made to detect and extract text and create new information with translated text.
TeamsHub.io Recommendation Engine to FIND What You’re Looking For
Understanding the trends of building super-intelligent applications using AI, TeamsHub.io is geared up to empower Microsoft Teams with the cognitive search capability further.
Yes, TeamsHub.io is going to awe you by making Teams more interactive and smarter for you with the upcoming Real-time Recommendation Engine that uses knowledge mining to deliver quick and personalized search results.
Here’s how – The TeamsHub.io recommendation engine will track user behavior by reading the number of clicks and visits to a page for a product, video, news articles, etc., and will load it to Azure Databricks and then train the Azure Kubernetes Service model using rating and ranking metrics to display top 10 recommendations for the user.
TeamsHub.io and Content Research
TeamsHub.io will make you capable to search technical data without having to sift through the dense materials from page to page. In the process of content research, the user first ingests technical content as unstructured and structured data via product guides, manuals, and other documents in the first phase of the data flow. Then, the content is enriched with AI using techniques such as key phrase extraction, entity recognition, language translation, and so on. And finally, the user finds and explores the newly structured data via search, existing enterprise applications, or analytics solutions.
In a similar way, TeamsHub.io search recommender will also govern the following functional areas of your business:
- Auditing and risk management
- Decision analytics
- Business process management
- Enterprise productivity
- Contract Management
The findability of content across MS Teams is something that every user sincerely wants. And what’s a better way than taking the advantage of AI and let your system learn and suggest answers to user queries.
TeamsHub.io recommendation engine is designed to provide a coherent and cohesive search experience to your users. As a result, by enhancing search results and reducing the complexity of search, you can drive high user satisfaction, avoid operational overhead and scale easily with minimal investment.