Chatbot AI

Let the bots do the talking



Multilingual support can greatly increase the adoption of bots within various geographies where multiple languages are spoken. If targeting a global audience, leveraging a chatbot that the ten most common languages will open up conversations to more than three billion people worldwide.


Context-based responses

Context identification is achieved by analyzing the customer’s profile and chat history. Our chatbots take it a step further by personalizing the chat based on the user’s real-time activity. Our advanced NLP capabilities can even recognize the common spelling and grammatical errors and make the chatbot to interpret the user’s intended message.


The human touch

With advanced sentiment analysis algorithms, AI systems understand your customer's emotions and respond with empathy. Our chatbots are capable of identifying customer frustration, and even positive moods and act accordingly. These systems also collect useful customer data from customer interactions and automatically add them to the customer profile. They later use it to personalize the chat.


Performance monitoring

Once you get your chatbot running, you need end-to-end visibility into performance and issues affecting chatbots. Fortunately, there are well-defined metrics to measure your bot’s performance. The top key performance indicators (KPIs) include active users, session length, user ratings, fallback responses, etc. MindGlow's chatbots come with in-built monitoring tools.


Fall-back responses

Chatbots invoke fallback responses when cannot find an appropriate response to a user’s query. Monitoring the frequency of fallback responses will help you to identify knowledge gaps and faulty NLP. You can then train your chatbot NLP to recognize the variances in which users phrase an inquiry. It is wiser to pick a chatbot platform that comes with built-in analytics to avoid the hassle of setting up analytics using third-party services.


Confusion triggers

Even bots with the most advanced NLP might not understand everything that a user says. But fortunately, ‘Confusion triggers’ is a metric that identifies when a chatbot cannot understand a message and indicates how and where a chatbot needs to be improved. Confusion triggers will help the bot delegate the task to a human agent after a failed interaction.


Middleware engine

Middleware engine enables you to hook custom integration logic into the different parts of the chatbot lifecycle. Our middleware engine is really flexible and the core features capturing, categorizing and storing messages, automatic logging, and processing user inputs from various channels. Also, the solution enables you to build chatbots fast and manage them effectively at scale.


How It Works

  • Consult

    This is where we sit down, grab a cup of coffee and dial in the details.

  • Create

    The time has come to bring those ideas and plans to life.

  • Develop

    Whether through commerce or just an experience to tell your brand.

  • Release

    Now that your brand is all dressed up and ready to party.

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