At EdgeTier, we provide a powerful feature that allows you to access your interaction data through a PostgreSQL database interface. This option is ideal if you want full control over your data to create custom reports. Direct database access can be leveraged with analytics tools such as Tableau, Metabase, or any other reporting software that supports SQL.
If you prefer a hassle-free solution, we can host the database for you. Once configured, we will provide you with all the necessary credentials to access the database. This is the simplest option, requiring minimal effort on your part. To get started, simply provide us with the set of IP addresses that will be used to access the database, and we’ll handle the rest.
Alternatively, if you prefer more control over your data infrastructure, you can choose to host the database yourself. In this case, you will need to share your database credentials with us, allowing us to securely write to the database. This option gives you full ownership of your data while enabling you to benefit from the custom reporting capabilities we offer.
Your view will include every analysed interaction from your EdgeTier instance, each with the following attributes available:
| Attribute | Description | Type |
|---|---|---|
interaction_id |
Unique identifier for the interaction | uuid |
interaction_type |
Channel type name (e.g. Chat, Email, Call) | string |
interaction_type_id |
Numeric identifier for the interaction channel type | integer |
agent_email |
Email address of the agent who handled the interaction | string |
agent_id |
Unique identifier for the agent | uuid |
agent_name |
Display name of the agent | string |
agent_tags |
Tags/labels associated with the agent (e.g. team, location, skill group) | array |
auto_tags |
AI-generated tags automatically applied to the interaction based on content analysis (e.g. Contact Reason) | array |
contact_email |
Email address of the customer/contact | string |
contact_id |
Unique identifier for the customer/contact | uuid |
contact_name |
Display name of the customer/contact | string |
contact_phone |
Phone number of the customer/contact | string |
create_date_time |
Timestamp when the interaction record was created | datetime |
end_date_time |
Timestamp when the interaction ended | datetime |
external_reference |
Reference ID from the source system (e.g. CRM ticket number, chat platform ID) | string |
has_confusion |
Boolean flag indicating whether customer confusion was detected | boolean |
has_frustration |
Boolean flag indicating whether customer frustration was detected | boolean |
has_gratitude |
Boolean flag indicating whether customer gratitude was detected | boolean |
has_praise |
Boolean flag indicating whether customer praise was detected | boolean |
language |
Full name of the detected language | string |
language_id |
Numeric identifier for the language | integer |
language_iso_code |
ISO 639 language code (e.g. en, fr, de) | string |
phrase_tags |
Semantic tags applied automatically via phrase trigger rules | array |
segment_tag_id |
Identifier for the tag that limits data access from some user segments | uuid |
start_date_time |
Timestamp when the interaction started | datetime |
subject |
Subject line or ‘title’ of the interaction | string |
summary |
Brief AI-generated summary of the interaction content | string |
system_tags |
Tags applied by system-level rules and classifications | array |
update_date_time |
Timestamp when the interaction record was last updated | datetime |
variables |
Custom key-value metadata passed in from the source system | json |
transcriptions |
Full message transcript of the interaction (e.g. the full transcription of a call interaction) | json |