Nebuly product Changelog

May 06, 2024

Feature

Enhancement

Customize your end-user intents

Select one of the predefined suggestions

You can now fully customize the intents generated by the Nebuly platform. You have the option to create a new intent to track a specific user behavior, or you can merge two detailed intents into a new intent that better suits your specific needs.Merged intents inherit all the warnings and interactions of the original intents. Newly created intents look back over the last 60 days of interactions to find occurrences of the defined intent.

New & Improved
-The UI of the warnings page has been refreshed, including the addition of a new table for the user-defined rules, providing a much clearer picture of the different warning detection rules.
- Added the possibility to filter the interactions in the user intent details page.

Fixes
- Fixed bug not showing any result when searching over filter values for custom tags
- Now global filters apply on retention chart as well.

May 03, 2024

Feature

Enhancement

Custom Warning Categories 2/2

Define your own warning category

You can now decide what type of warnings are relevant to your business and define your own warning category. This gives you full control over the type of warnings tracked on the platform.

Apr 29, 2024

Feature

Enhancement

Custom Warning Categories 1/2

Select one of the predefined suggestions

In addition to the custom warning category, we are also releasing the warning suggestion feature. Warning suggestions give you an overview of the most impactful warnings that the platform has automatically detected from your user interactions. You can then decide to accept the suggestion and turn it into a warning category, or mark the suggestion as irrelevant. This allows the platform to adapt to your needs and provide more relevant suggestions in the future.

New & Improved
- New simplified external endpoints to get the warnings generated by the platform

Fixes
- Fixed a bug in the global filters that displayed the wrong number of interactions next to the suggested filter values.

Apr 22, 2024

Feature

Enhancement

Increase visibility on trending intents

Now you can sort the user intents in the user intelligence page by most trending other than by number of users and number of warnings. We also have refreshed the UI, with a cleaner view on the user intents.
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New & Improved
- In the overview page you can now see how the trends evolved respect the previous month
- It is now possible in the overview page to change the time-range you want to get the overview on

Fixes
- Fixed a rare issue showing the same warning both as LLM related and not LLM related

Apr 16, 2024

Feature

Enhancement

Global filters

Filters that stay on as you navigate

With our latest update you can use global filters that are shared across the platform pages. These filters are particularly useful when you want to analyse your data about a specific user group.

New & Improved
- The external endpoints that can be used to embed our overview, user-intelligence and warnings pages have been updated considering the latest platform UX. Find more info on our Docs.
- The overview, user-intelligence and warnings pages have a refreshed UI
- The Navbar and the main platform components feature a redesigned UI

Fixes
- We fixed a bug in the intent computation that was creating new intents for newer interactions, even when the same intent already existed.

Apr 12, 2024

Feature

Enhancement

Intent search and a new user warning category

Search your users intents

Now you can simply search over all the intents and apply filters. You can easily find the information you are looking for in a matter of seconds.

We also added a new “Harassment” category to user warnings. This category shows when the user is trying to harass the model or cover some not-allowed topics like asking for explixit sexual content or asking for dangerous information (like building a bomb).

Apr 05, 2024

Feature

Enhancement

Update on user warnings

We grouped user warnings into 4 categories

1. Business warnings: valuable customer insights on what you can improve in your product and business
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2. Lack of personalization: users do not find the model responses tailored to their specific user profile. This may be because the answers are too complex or simply not relevant to their needs.
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3. Wrong information: users complain about information being wrong.