The most ideal way to bootstrap your chatbot building process is to employ ‘Flows’, where the Bot...
How to build a chatbot 101: Expected timeline
“How long will it take to build and deploy my chatbot?”
A question that scares most Conversational AI providers in the market today!
The fear stems from the working knowledge that this particular question does not always have a straight answer.
Conversational AI providers will claim that their AI virtual assistants can be ‘Built quickly’ or is a ‘Quick-deploy solution’. However, it rarely is.
When Conversational AI providers say that the time to deploy is 6-8 weeks, they say that without talking about scale.
It’s a known fact that the time taken to build, train, test and deploy chatbot changes according to the scale of usability. For larger enterprises, a higher number of employees or vast business functions, a single chatbot could take between 4-12 months to be fully ready for deployment.
One of the most important steps in the chatbot building process is creating a robust knowledge base, which forms the backbone of a chatbot.
What is a knowledge base?
A knowledge base acts as a content repository that helps the chatbot formulate responses. All the content relevant to the business, vertical or function needs to be added to the knowledge base so that the chatbot can extract data and formulate responses. In simpler terms, the knowledge base contains all of the information, content and data that will be used by the chatbot to create accurate responses.
Even if the Conversational AI provider managed to build an AI-powered chatbot quickly, an incomplete knowledge base would render the chatbot ineffective.
Creating a knowledge base from scratch is one of the most time-consuming steps across the chatbot building process. Large scale enterprises and businesses with diverse products/SKUs are every Conversational AI provider’s nightmare.
Enterprise data and information are usually spread across thousands of web pages and documents. Collating all of this information, segregating it and then sorting it is a monumental task of sorts.
Even with a team of skilled developers working round the clock, extracting all the data and verifying it could take anywhere from 4-12 weeks.
And by default, the overall costs also rise. The total Full-Time-Employment (FTE) hours x the number of skilled developers required to complete this step ends up costing thousands of dollars. This is apart from the development and testing costs that also need to be borne by the customer.
The traditional practice of building a chatbot still relies on the manual aggregation of data, which is costly and inefficient. In today’s global marketplace, businesses rarely have the time to invest in chatbot development. They require solutions that are actually ‘quick to deploy.
However, in the case of chatbots, the promise to build and deploy quickly is conditional as knowledge base creation continues to be an unpredictably long process.
As a leading Conversational AI player in the market today, we at Enterprise Bot decided it was time to resolve this age-old problem. Our latest offering is a product that uses intelligence to automate the data extraction process.
Our AI-powered parser crawls through thousands of web pages and documents to accumulate relevant information, which is used to flesh out a conversational knowledge base.
How long would it take? Just 24 hours (1 Day).
If you’re interested to know more about this offering, reach out to us at firstname.lastname@example.org
And if you wish to know more about our other products and services, visit our website.