AMI, an AI-Driven Bot that will help you increase revenues 25%

Build once and deploy anywhere. AMI never misses a sales opportunity and never keeps your customer waiting

Features:

Integrate with any major eCommerce platforms

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Actively engage EVERY customer

Built on state of the art deep learning, AMI sits at the top of your store to prompt customers to engage and then respond to customer queries.

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Scale as you grow

You can start with limited features, and add more to cover your user journey later such as match intents to actions, use APIs with a webhook or build decision trees

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AMI will help you LEARN about your customers

Analyze conversation data and optimize inline with your business KPIs

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Your data is secured

You own your customer data. We follow stringent data privacy policies.

Make AMI smarter by integrating her with data from other platforms

Use Cases

Customer service

AMI responds to customer requests instantly-whether simple or complex. We have a bot-human hybrid model to handover the response to best customer care expert.

Marketing

AMI can be deployed on any messaging platform. It helps broadcast your products and services to the world through a conversational interface.

Store

Modern retailers need to deliver wonderful customer experience. AMI will help you in product search, product recommendation, shipping information and order status update.

IT automation

We provide prompt IT service through our bot as it supports a third party ticketing systems like ServiceNow to handle service requests, submit tickets and related actions.

Case Study

A US based manufacturing giant specialized in PCBs

Challenges
  • The distributors and retailers contacted the client by a customer care number for enquiring about account balance, shipment status, payment dates etc.
  • Number of calls per week range was between 200 - 300 and it went on to 500+ depending on day of the month.
  • Some dedicated resources only were involved in addressing the support issue which led to increase in cost up to 15%.
  • This also gave an impact on overall productivity i.e. productivity was reduced by 20-25%.
Dimensions Solution
  • The distributors and retailers contacted the client by a customer care number for enquiring about account balance, shipment status, payment dates etc.
  • Microsoft LUIS framework used to develop Chatbot solution absorbed user inputs and identified intents and entities to be used by Chatbot.
  • Azure hosted SQL Server with the UMLS Meta thesaurus queried database using identified intents and entities.
  • The backend component processed responses and guided interactions with the user, as well as acted as the middleman between the NLP and Database.
Benefits
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  • Support response was increased by 80%.
  • Disengages resources from mundane transactions to focus on more complex accounts increase overall productivity to 76%.
  • Support calls reduced by 60% per week
  • Chatbot implementation reduced support overheadcos to $6000 per week.