Airy Core allows you to connect many different sources: our Live Chat Plugin, Facebook Messenger, WhatsApp, or your own custom sources.
One of the crucial features Airy Core provides is the ability to process conversational data from a variety of sources such as Facebook Messenger, Google Business Messages, Twilio.WhatsApp or Twilio.SMS.
You can connect sources through API requests or using our Connectors UI. Our Sources guides cover both options, step-by-step.
It's important to understand the difference between a source and a channel. A channel represents a connection between a source and your Airy Core instance: multiple channels can thus use the same source for different conversations.
Connecting a channel allows the possibility of starting a conversation between a source and your Airy Core instance. Once a channel has been connected, your Airy Core instance will start ingesting messages and create new conversations accordingly.
You can connect as many channels as you want for each source. The Inbox UI displays all of your conversations from all of your sources.
With the Control Center UI you can connect your connectors via UI
#How it works
The ingestion platform processes incoming webhook data from different sources. It then makes sense of the data and reshapes it into source independent contacts, conversations, and messages (see our glossary for definitions).
Of course, due the very nature of the problem, the code is very specific to the thirty-party source it deals with. This frees you from dealing with these integrations yourself.
While sources are all different, their architecture follows a few key principles:
The webhook integration ingests payload data as raw because you get it in a source specific topic.
We only extract metadata from the source data as we translate events into conversations and messages. The content is not parsed at ingestion time, we let it travel untouched through the system.
These principles allow you to reprocess data from a conversation platform at any given point in time. If the data pipeline has a bug (eg: the messages are counted incorrectly), you can reprocess the data and fix a bug for past data as well.