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AI Engine explained – The path to smarter automation

Have you heard of the term “AI engine” yet? If not, it’s definitely time to familiarize yourself with it. An AI engine is like a Swiss Army knife for businesses that utilize technology. The engine includes a variety of tools and methods that enable computers to perform tasks that have, until now, required human intelligence. This could be anything from understanding natural language, recognizing items in data, or making decisions based on complex scenarios. The final output from the engine is clear ready-to-use data that can be consumed easily by humans or machines.

Why Do You Need an AI Engine?

The magic of the AI engine lies in its ability to leverage the vast and diverse world of artificial intelligence, making it accessible and usable for your business's specific needs. It's like having a team of robot geniuses at your disposal, ready to take on any data-driven challenge you throw their way.

Whether you're a small business founder or a senior executive in a large company, integrating an AI engine can change the way you automate processes, analyze data, and interact with your customers. It's about making your software smarter, your decisions faster, and your business processes smoother.

How Does the AI Engine Work?

Imagine you have a pile of Lego bricks (your data) that are not in any particular order. The data can be in various forms: text, reports, pictures, sound, and even video. The AI engine acts like a master builder who knows exactly how to assemble these bricks into a masterpiece (structured, functional insights) based on the plan (instructions) you provide.

Through its interface, you can "talk" to the engine, asking it to perform complex tasks such as going through customer feedback, automating email responses, or even identifying trends from large data masses. You just need to provide the raw data and instructions, and the AI engine takes care of organizing it into a form that's meaningful to you. This is, of course, a part of a process flow that is automated: you will not be hand-crafting these instructions and data or sending them to the engine manually, it is all automated. You can focus to enjoy the final results.

Unstructured messy data is passed to the AI Engine that makes the data clear and usable.

Case study: AI engine for a renowned SaaS product

We implemented a customized AI engine for our client, transforming work that previously required manual human labor and typing into a simple press of a button. By pressing the button, the AI engine starts up and automatically processes the data fed into it.

The AI engine extracts essential information from seemingly disorganized data based on the instructions given to it and produces a result in a file format that is understandable by the machine. This file is used to streamline the user interface of the SaaS product.

Before the AI engine, users had to manually search for information from various sources and enter it into the system themselves. As a result, the system often ended up with incorrect information, such as duplicated data and misspelled values. Additionally, the process took several minutes – now, the AI handles the work in a few seconds, and the user can simply glance through the information and focus on what's important.

Making this all work fast enough requires various optimization techniques. The user experience cannot be sacrificed for the sake of AI. There are many ways to optimize the speed, but one of the most meaningful ones are prompt engineering and concurrent programming. With advanced prompt engineering, we can squeeze more speed out for example from LLM models. While prompt engineering sounds easy, it's not. The prompts change from model to model, and making them work optimally is achieved only via the practical experience we have gained during the last two years in our other projects.

Most automation flows that AI engines execute consist of multiple tasks that are executed concurrently. On multi-core machines, parallelism should be utilized. Concurrent execution might not always be possible due to the automation flow structure. However, concurrent programming patterns cannot be avoided when aiming for the best speed. This is especially true in multitasking agentic automation flows: agents and their tasks are run concurrently.

This is just a small glimpse into how the AI engine can be utilized. Transforming messy – albeit human-understandable – data into structured data is, in any case, one of the most useful applications of AI.

How Do I Get Started?

The beauty of AI technology is that it has become increasingly accessible and is integrated into the tools we use daily. The first step in leveraging AI is to understand which areas of your business could benefit from smarter automation. From there, it's about deploying the AI engine, that is, integrating it into your existing software. If a ready-made AI engine, like our YOKOT.AI, does not fit your use cases, the AI engine can be fully customized. In that case, the entire engine's management and development remain entirely in your hands.

Remember, integrating AI into your business is not about replacing humanity; it's about enhancing it. By automating routine and data-intensive tasks, your team can focus on creativity, strategy, and human-centric tasks.

At Softlandia, we are pioneers in AI engines and applied artificial intelligence. Contact us to bring your automation and processes into the 2020s!