Companies are using chatbots more and more in corporate communications. Therefore it is of growing importance to understand how chatbots work and how they can be implemented.
Before implementing chatbots in the organization, it is worth taking a look at the technical infrastructure behind the bots. Bots can be programmed and trained in two different ways: rule-based and self-learning.
There are several ways to develop and implement chatbots within an organization. They can be roughly broken down into the following three approaches.
In this approach, an organization programs the bot mainly from scratch and only uses a few small building blocks (“libraries”) contained in the programming language. The bot can be tailored to the company’s existing technical infrastructure.
More often companies collaborate with an external specialist in chatbot systems. Often these are start-ups dedicated to the specific field of conversational automation. Even large companies work on the basis of these external services as they neither have the capacity nor see the need to build their own systems.
The most practical way to implement a chatbot is to rely on existing frameworks from large tech companies. Several such frameworks exist for different purposes. The best-known examples are Microsoft Azure, Google Dialogflow, and IBM Watson.
When implementing these systems, companies can also work with start-ups. They often offer specialized solutions built on these large-scale frameworks and have prior experience of implementation.
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Bot or not? The facts about platform manipulation on Twitter. blog.twitter.com/en_us/topics/company/2020/bot-or-not.html.