What Industries Can Benefit From Vertical AI?

Vertical AI is one exciting new trend in the Artificial Intelligence industry. An AI startup offers a customizable product based on Artificial Intelligence, owning all the workflow to satisfy specific customer demand. 

These companies develop an entire solution from beginning to the end, starting with clearly understanding the business need to tracking real-time product performance. From there, they build the system to deliver clear answers to frequently asked questions and create recommendations to optimize growth. They do it all by leveraging data and using advanced technology. This results in delivering new and innovative products that are rooted in proven Artificial Intelligence.

Key Facts about AI

The vision of this vertical AI is to build machines that can think like people at a low level. Companies involved in vertical AI startups are building systems that can quickly learn many different types of knowledge, including: 

  • natural language processing
  • speech recognition
  • web search engine optimization
  • customer relationship management
  • machine vision

At higher levels, the machines can anticipate user requirements and can make choices that would have traditionally been a human undertaking. In short, these systems can think, reason, and interact with humans at a completely new level.

The vertical AI market is still very much in its infancy, with most vertical AI systems built on big data. Companies are marrying vertical AI platforms with their existing vertical-specific content to build better products and services for their customers. These vertical algorithms are often coded through rules-based systems to facilitate compliance with data privacy laws and other regulations. New artificial intelligence systems are emerging every day, each one more innovative than the previous. Vertical AI startups are using machine learning techniques to ingest knowledge from across different industries so they can be applied to an endless number of vertical niches.

How Vertical AI can be Used?

The key to using artificial intelligence effectively is to design a solution that leverages multiple data sources, including text, videos, pictures, audio, and speech. Additionally, deep learning frameworks must be available for use with large databases and applications. The final step is to apply the knowledge to problem-solving. As this concept is relatively new, many entrepreneurs are hesitant to invest in the technology because of a lack of proof of performance so far. However, companies involved in vertical ai startups are continuously collecting and deploying data to provide customers with a full range of personalized services.

One way in which artificial intelligence can be applied in decision-making is through rule-based engines. Rule-based engines are a set of software that can enforce rules and regulations based on input. For example, if a customer requests that the restaurant in which they eat a dinner meet certain requirements for serving their food, an algorithm can be developed to comply with the request. Once this is successfully implemented, it will continue to find new rules to apply to new situations. Such a system could then be modified to allow for special requests from individual clients. This form of artificial intelligence can be used to create scheduling features, which allow the restaurant to prioritize the menu, create limitations on food quantities, or even determine minimum acceptable temperatures.

Machine Learning and Proprietary Data

Another application of vertical AI is machine learning. Machine learning refers to the process by which computers can achieve expert status in tasks without constant supervision. In this case, the machine is capable of recognizing patterns and determining appropriate actions. As this concept is still fairly new, many people are skeptical about investing in venture capital to invest in these programs. However, there is a lot of money to be made with this technique. It has already been used to train people in various fields including finance and insurance. It is also expected to play a major role in the financial industry over the next few years.

The third use of vertical AI is to take a critical look at proprietary data. For example, proprietary data typically includes three main components: 

  1. financial statements
  2. technical analyses
  3. marketing plans. 

Many times, these data have a significant effect on the overall business value. In fact, by removing all non-employee access to this proprietary data, an enterprise can increase the value of its business and reduce the risk of large-scale data leakage.


Vertical AI has the potential to significantly increase efficiency across the board. However, for these benefits to materialize, discipline must be exercised when it comes to the use of machine learning algorithms, and executives must ensure that these rules-based engines do not break any laws or regulations. As such, the financial services industry appears to be the most attractive area for a business to explore. Therefore, if you are planning to apply artificial intelligence to your company, this sector holds several promises.

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