This article will give you a general idea of how AI might be integrated with your Betty Blocks application.
After reading this article you’ll know:
-
What kind of flow can be created in the application powered with AI
-
The use case example of such flow
-
Future business benefits of AI integration
Since artificial intelligence (AI) appeared in our technology landscape, the platforms are reshaping how businesses operate and interact with their products and customers. As a Betty Blocks user, you can experience the advantages of integrating AI in the near future. In this article, we’ll figure out how the AI flow is going to work within applications by looking into a step-by-step application of one of the use cases.
Use case: semantic search
Imagine the potential of creating an AI-driven semantic search tool within your Betty Blocks application. Let’s say, your company has an internal web application to store important documents, like contracts with your clients. It might store thousands of documents, making it rather difficult to find the desired information in them, even if you use some keywords. That’s why an integrated semantic search comes into action enabling you to search for certain information using the algorithms that understand the context and meaning behind the queries.
What does this kind of application have under the hood? First of all, you have to build a new page with a simple form that sends the data to your action. From the front end side, it will look like a web page with a search field where you type in your request. For example, you can type in ‘artist fee’.
This request goes through the action flow that consists of machine-learning action steps. As documents are indexed, AI calculates the distance between your query (search request) and these indexed documents. So it not just uses the keywords, but also looks for words that are semantically related to ‘artist’ and ‘fee’: ‘concert’, ‘event’, ‘payment’, ‘wage’, etc. In other words, semantic search AI can understand the context of words or phrases by measuring the distance between them and picking up the most closely related ones to find the best-fitting variants and present them to you.
Example of document search flow in the action builder
The action communicates with the data sources you have configured to gather your data. The data gets compiled and returned to you in the form of extracts of documents that contain similar information that you are looking for.
Using integrated document management systems HighQ or iManage along with your AI semantic search tool, you can enable your application to support popular text formats (PDF, TXT, DOC) so that texts are easily converted and used.
Why choose AI?
Choosing AI integrations and allowing business technologists to configure them can bring lots of benefits to a business. You will be able to build solutions to unique needs or pain points, experiment with different approaches, and respond to your customer requirements way faster.
Working with data using AI technology has never been easier. Both you and your customers will definitely see instant gratification from more speed, automation, and agility. AI potential is rather difficult to measure, but it’s clear that this technology is here to stay, and the quicker you embrace it, the more value it can bring to your business shortly.