The previous blog defined conversational artificial intelligence (AI) and its common enterprise use cases.  This final chapter of the series will explore the core, foundational technological piece that drives organizational artificial intelligence—the Enterprise AI platform.

In this blog, we’ll cover:

  • What is an Enterprise AI platform?
  • How does it work?
  • What can an Enterprise AI platform accomplish?
  • A look at Veritone aiWARE

What is an Enterprise AI platform?

As we defined in the first blog in the series, Enterprise AI is a category of business artificial intelligence that deploys machine learning and cognitive capabilities. An Enterprise AI platform enables organizations to implement these capabilities throughout the business and build and deploy new Enterprise AI software. 

Companies across the board understand the importance of AI in moving beyond the initial steps of digital transformation. But when they hear the word “platform,” many worry that it’s a massive commitment to scope, deploy, and train their teams to use such technology.

However, an Enterprise AI platform should come with the flexibility to integrate with other systems in their technology stack and data practice. In many cases, it’s not a complete rip and replace of existing systems. Instead, the platform can provide cognitive engines and capabilities to enhance solutions.

How does it work?

An AI platform is a set of services with multiple layers that completes the machine learning lifecycle that moves through seven key phases:

  1. Gathering Data: the platform collects data from various sources via an integration layer.
  2. Preparing Data: once the data is collected, it’s prepared for processing.  
  3. Wrangling Data: as an additional preparatory stage, data is cleaned so that analysis is not working with broken or inaccurate data sets.  
  4. Model Training: with clean data sets, models can then be selected to run it through.
  5. Model Testing: typically, multiple models are tested in processing the data to help determine which model performs the best.  
  6. Model Deployment: the cognitive model is then deployed and monitored to ensure that it can scale up and down as needed and avoid bias.
  7. Data Analysis: insights can then be extracted from the data processed by the cognitive models.

What can an Enterprise AI platform accomplish?

An Enterprise AI platform acts as the technological foundation to accomplish two key things:

  1. Deploy AI Across Legacy Enterprise Applications   
  2. Build New Enterprise AI Applications or Solutions  

As a result of these two functions, companies are able to produce previously unrealized insights from hard-to-reach sources such as images and videos or from edge devices. At the same time, the platform enables organizations to intelligently automate processes, maximizing the capabilities of their current staff, making their departments run more efficiently backed with the data for better decision making. 

Deploy AI across the enterprise
The platform serves as that critical lynchpin to tie together legacy systems so that data has a single destination. In addition, given the ingest capability an AI platform offers, legacy systems can become even more intelligent once more robust AI capabilities are introduced.

Unlike other solutions that might come with limited AI capabilities, an AI platform takes it to the next level in terms of flexibility and scalability. As the enterprise grows or pivots, an Enterprise AI platform typically can scale up and down with a company’s business needs at any given time. In addition, an organization can deploy it in various ways and with their preferred infrastructure providers.

Produce previously unrealized insights and intelligently automate processes
A platform can connect disparate systems and enhance them through an integration layer by ingesting AI capabilities to extract previously unrealized insights and automate data-centric processes. For example, one of the areas that companies often don’t have insights into is their unstructured data. Contained within images and video is an abundance of data that can be used to increase asset visibility and organization and enable improved decision-making and content review automation.

Build new Enterprise AI applications or solutions
While the capabilities of an AI platform can solve many challenges that companies are aware they have, it also enables a newfound ability to solve new or uncovered problems. Building and deploying new applications and solutions on top of an Enterprise AI platform future-proofs these new technologies to keep up and leverage the latest developments in AI.

It also bakes in the scalability and flexibility required to keep up with changing landscapes across different verticals. From Web 3.0, commonly called the metaverse, in media and entertainment to managing distributed green energy systems, companies can continue to evolve with new developments in respective spaces, using a foundational future-proof platform.

A look at Veritone aiWARE
Veritone aiWARE, a hyper-expansive Enterprise AI platform, makes it easy for developers and systems integrators to rapidly build, scale and operationalize AI-enabled applications. Helping organizations acquire, analyze and act on hard-to-reach data (video, audio, images, text), it automates content-centric processes for greater business efficiency and insight. Unlike point solutions, aiWARE offers a full stack of ingestion adapters, best-of-breed AI models, a data lake, low-code workflow and integration tools, as well as vertical apps that accelerate enterprise AI implementation and adoption.

aiWARE offers organizations a low barrier to entry in adopting an Enterprise AI strategy, connecting current applications and solutions and bespoke creations on a single platform. Containing an ecosystem of over three hundred best-of-breed models, aiWARE provides a means to rapidly deploy AI for audio transcription and translation, face and speaker recognition, object detection, text analytics, data correlation, and a host of other cognitive capabilities. In addition, you can integrate existing AI models right onto the platform.

aiWARE simplifies and reduces much of the manual burden placed on data teams and reduces the costs to conduct scalable data acquisition, analytics, and action. Through aiWARE, and the Veritone AI solutions team and partner network, organizations can start unlocking the full potential of their data practice across solutions and applications.

Learn More About Veritone aiWARE Today