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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.
\nToday, businesses worldwide are embracing advanced Conversational AI solutions to automate customer-facing touchpoints. From social media platforms and websites to apps and voice assistants like Google Home, conversational AI solutions are everywhere.\nThe AI-driven conversational platforms help to develop advanced conversational interfaces such as voice bots, voice + text assistants, and chatbots. These intelligent digital assistants provide Guidance, Recommendations, Advice, Consultation, and Expertise (G.R.A.C.E.) which isn’t possible in a “self-service” buying journey.
\nRecent market research shows the global conversational AI platform market is predicted to grow at a CAGR of 32.4% during the forecast period of 2019-2025. With this surge of Conversational AI platforms, the challenge now for many businesses is not about integrating Conversational AI. Rather, it is about selecting the most appropriate conversational AI platform to match their unique business requirements.
\nConversational 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.
\nFor example, in the context of eCommerce, Conversational AI can be deployed to achieve multiple aims, including customer acquisition, buyer engagement and customer support. However, when deployed within the enterprise, the same tools can be used to improve productivity, implement lean operating practices and drive greater collaboration between teams. As an enterprise, you need to determine which capabilities will work best for your business.
\nTo decide which conversational AI platform is right for your business, you must start with the following:
\nAs you narrow down to the many ways Conversational AI can add value to your business, consider which areas of AI best fit into your organization and how to select the right implementation partner.
\nEvery organization must choose the platform that matches their needs, depending on where they are in their journeys. No two organizations can have the same business and technical requirements. Hence, it’s important to get in touch with the right vendor who can determine the scope of your business and offer a conversational AI platform whose features will meet all your requirements.
\nDeeply 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.
\nOn-premise deployment - For tighter security
\nOn-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.
\nCloud deployment - For greater flexibility & lower cost
\nConversational 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.
\nHybrid deployment - For seamless integration
\nAnother way to deploy Conversational AI is hybrid-cloud. In this model, production infrastructure is on-premise and processes like Conversational AI-training 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.
\nAnother 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.
\nBased upon Conversation AI’s broad applicability, we can arrange the vendor landscape as described below:
\nAnother key conversational AI differentiator lies within the features and capabilities of the platform. Currently, chatbots can be deployed on relatively simple rule-based principles or more complex AI-based platforms.
\nThese classifications offer insights on how to evaluate, procure, and implement conversational AI solutions into your business and compare the different offerings at different layers in the stack.
\nAfter selecting one specific Conversational AI platform, you need to check if you are adopting all the right features into your business.
\nCan the Conversational AI solution guide the customer through the purchase journey by delivering status clearance pop-ups, notifications, reminders, cart abandonment messages, or internal mailers?
\nCan the solution be integrated with third-party channels?
\nIs there a limit on customization – limitation of the training data, character limits, user experience/ user interface restrictions, or backend integration capabilities?
\nCan the Conversational AI platform map the conversation flow/design and use smart algorithms to minimize ‘unanswered questions’?
\nCan the Conversational AI be deployed on-premise, pure-cloud or hybrid?
\nHow seamless is the API integration of the AI platform with legacy systems?
\nIf you are wondering whether one Conversational AI platform can provide you with every solution, then the answer is yes!
\nSenseforth’s proprietary platform A.ware provides pre-built, pre-trained extensive industry and functional AI models for various industries and domains. We are a full-stack service provider and allow our clients to self-host or integrate the Conversational AI on a public or hybrid cloud.
\nAt Senseforth, we understand chatbots represent the next wave of user interaction for a wide range of use cases. Accordingly, we have developed both bots by function and bots by industry using A.ware. Our bots can be configured to suit various indicators and events like source, landing page, idle time, customer behavior, transactions performed, customer preferences, profiling, and point in the interactions journey.
\nAll our Conversational AI integrations have bi-directional communication capabilities. They come with pre-built integrators for different CRM, Ticketing, Email, HRMS, ERP, Order Management systems using REST API, web services or RPA tools. When it comes to integration with third-party channels, solutions built using A.ware can be easily implemented across social media channels, IMs, voice-enabled assistants, mobile apps, and other collaboration tools.
\nOne of our core beliefs is that as the business scales, so does the scope of implementation and improvisation. Our Conversational AI platform allows you to develop interfaces that can be customized to go beyond training data by learning and inferring knowledge and can be implemented to unseen data sets. So, at Senseforth there are no limits on UI customization, number of intents, entities, responses, languages or integrations.
\nSome of the chatbots which we have developed using A.Ware are tailored to provide solutions to specific operations as well as specific industries:
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