Conversational AI Platforms use natural language understanding capabilities to facilitate human-like conversations via voice, text, touch, or gesture input. They provide the artificial intelligence models required to build intelligent bots for various business requirements.

What Conversational AI can do for your business?

Conversational AI platforms can be used to build a range of conversational interfaces - with capabilities to handle complex processes to simple if-else loops that guide users through a flowchart. While any investment in conversational AI is expected to yield significant competitive advantage and improved financial returns,it is not only about profit margins. The decision to implement Conversation AI should be based on well-defined goals and objectives.

Classified by deployment

Deeply integrated into information systems, conversational AI platforms can communicate with most channels, including voice interfaces, text messaging, social media, and websites. Depending on the nature of your business, you can choose how to deploy Conversational AI solutions - on-premise, public cloud, or hybrid. If you want a knockout post about Conversational AI, browse around here.

On-premise deployment - For tighter security

On-premise deployment of conversational AI ensures overall control over security measures and gives you the flexibility to allow access or restrict anyone from accessing your data. In this model, an enterprise uses proprietary architecture and maintains its own data centres. It offers options to customize and to integrate the solution into existing workflows. However, on-premise deployment of Conversational AI comes with certain restrictions, especially integration with popular third-party applications and software.

Cloud deployment - For greater flexibility & lower cost

Conversational AI deployed on the cloud comes with a lot of flexibility and is relatively less expensive than on-premise deployment. In this model, enterprises don't have to maintain servers in-house. It also ensures that enterprises have continual upgrades in the solution and access to pre-built machine-learning APIs instead of building their own.

Hybrid deployment - For seamless integration

Another way to deploy Conversational AI is hybrid-cloud.In this model, production infrastructure is on-premise and processes like Conversational artificial intelligence and analytics are performed in the cloud. It supports the seamless movement of applications between on and off-premises infrastructure. Thus, it provides greater freedom at the infrastructure level while giving control over the conversational AI. At Aisera, you can find best conversational platform.

Classified by use case

Another important consideration is the types of industry models and engines offered by the platform.In the Conversational AI landscape, vendors cover the gamut from data science platforms enabled with machine learning capabilities to marketing automation tools that help optimize advertising. Without some sort of organizational framework, this vendor landscape would look like a confusing mess to an enterprise end-user or Conversational AI implementer. Based upon Conversation AI's broad applicability, we can arrange the vendor landscape as described below:

Function-specific platforms

Under this landscape, vendors provide conversational AI platforms that aren't aimed at a specific industry or class of industry problem. They provide operations intelligence, predictive analytics, decision support, virtual assistants (including voice assistants), intelligent document processing, and task assistant models of all sorts.

Industry-specific platforms

Here vendors provide platforms with domain-specific AI and cognitive models that are tailored to the specific industry needs. These Conversational AI platforms leverage a combination of AI, cognitive technologies, and deep domain expertise to address industry-specific challenges. In this category, the AI vendor classification is extremely diverse, with dozens of further categories and distinctions. These solutions are for industries that are generally accepted as "verticals": finance, healthcare, insurance, energy, and utilities. It also includes cybersecurity and physical security applications, sales and marketing, news and content production, education and knowledge management, and the like.