Developing Enterprise Chatbots for Instant Access to Asset Performance Data
Leveraging Amazon Lex and other AWS solutions to build enterprise chatbots that serve a diverse range of use cases for a large cleaning solutions enterprise
Srijan started working with the client in 2015, collaborating on an application that simplified the development of standardized marketing collaterals. In 2016, they started working to create a solution that would improve the efficiency of the client’s existing cleaning solutions.
The client’s primary products are cleaning chemicals and equipment. In addition to that, they offer equipment servicing, which is a key revenue stream for them. While the client does not manufacture the cleaning machinery, they do equip them with IoT sensors that transmit performance data and allows the client to automate servicing for their customers.
Srijan worked with the client to help onboard assets to the IoT ecosystem, and collect, monitor, and analyze sensor data from various customer locations.
The Srijan team helped create interactive data visualization dashboards that presented all this data, and allowed client stakeholders, and their customers, to analyze it is real time. This is what helped the client track equipment conditions across their customer sites, and automatically offer servicing as and when required.
While the dashboards were a great resource, they had a few drawbacks:
In order to work around these challenges, Srijan proposed the introduction of chatbots in addition to the dashboards. The chatbot was designed to deliver the following benefits:
The chatbot worked on an “asked-and-answered” approach. This eliminated the need to log onto a dashboard, and filter and manipulate the controls to find the data you need. The client can simply ask a query and the bot would analyze all necessary data to give a clear answer.
For example, by asking the chatbot, “How well are Customer X’s machines performing?”, the client exec could get an idea of:
Here’s a look at what kinds of information the bot can deliver:
The chatbot was made available via mobile apps, and could be used anytime, anywhere to access the information required.
Because the bot is easy to use and does not require people to look at and analyze a lot of data, it has seen increased adoption, both by the client, and their customers.
Besides real-time reporting, Srijan teams also created chatbot PoCs for two other use cases for the company:
Enterprise operations such as ticketing, travel resourcing, customer care, customer onboarding etc. could all be streamlined to save the company’s time and resources.
Field teams out for equipment repair and servicing could use chatbots to quickly access necessary information like technical specification and manuals. Any challenges they face during repairs could be directly addressed to the chatbots, and correct answers received. Also, with the help of AWS DeepLens a field team member can directly communicate with an offsite expert when stuck, as well as run machine learning models to allow the chatbot to master the process.
The Srijan team worked closely with the client to create a solution architecture that catered to all their requirements.
Some of the key technology solutions leveraged for the chatbots were:
As an Advanced AWS Consulting Partner, Srijan is currently working with enterprises across media, travel, retail, technology and telecom to drive their digital transformation, leveraging a host of AWS solutions. Srijan's expert team of certified AWS engineers are working with machine learning and natural language understanding to create interesting enterprise chatbots for diverse industry use cases.
Looking to develop an effective enterprise bot ecosystem? Just drop us a line and our team will get in touch.