Staffing Bot

  • Service

    Product Engineering

  • Client

    Arya

  • year

    2017

  • Available On

Challenge

Maintaining the conversation between the user and BOT, resolving out the queries by using results from various APIs and transferring the conversation from BOT to human agent in-case of complex queries.

Approach

Integrations and Development

Capabilities to integrate with various tools i.e. Slack, Hipchat and social networking platforms i.e Facebook, Telegram etc. Bot solutions for the web and mobile platforms according to the requirements.

Deep Learning

In this BOT processes inputs to understand the intentions in a broader context and employ various types of neural networks for this purpose. Therefore they are more capable and effective in managing conversation thus BOTs act as the virtual human..

Finite State Machine

Bots response according to the queries fed in them and involve complex pattern matching i.e. matching incoming strings (customer text) with pre-defined patterns, therefore, they can handle queries up to a particular limit. 

Tech stack

  • Rivescript
  • DialogFlow.ai
  • RESTful web services

Best Support

24*7 customer support thus provides smoother interaction, more satisfaction, increases in revenue by resolving the queries instantly and providing better services.


Cost Effective

Hiring a human for the customer support is expensive and it can handle only one or two at a time thus bots can solve this problem as one chatbot is equal to loads of employees and can easily communicate with thousands of customers at the same time.

a tagline indicating a problem was solved.

  • 99%

    happy customers

  • 80%

    increase in revenue

  • 2%

    churan rate