February 2026
Input and Output Token Variables
You can now track input and output token consumption directly in the report section and interaction table. Add the “Input Token” and “Output Token” variables to your charts to monitor LLM trace data. Note: these values come from what’s passed through the Interaction API, so if they aren’t provided there, they’ll appear as 0.Output Length Metric to Chart Variables
A new chart variable is now available to measure output length in characters, allowing users to track how verbose model responses are over time.New Failure Category: Thumbs Down
A new failure category has been added that automatically groups all interactions receiving a thumbs down into a dedicated category for easier analysis and reporting.Custom Variables for Analytics and Table Charts
Users can now define custom variables when creating or editing a chart. Custom variables support mathematical formulas, allowing customers to express calculations that were not possible with built-in variables. Formulas can reference both built-in and custom variables, and filters can be applied as usual, enabling businesses to track their metrics that matter most to their usage.January 2026
Nebuly-Langfuse native integration
We’ve launched a native integration that lets teams ingest Langfuse observability data directly into Nebuly for user analytics. What’s new:- Full integration option: Nebuly automatically pulls traces from your Langfuse account daily (interval configurable). API keys are securely stored in encrypted vaults.
- Local integration option: Use open-source Python scripts to extract and transform data in your own infrastructure. Full control over data residency and enrichment.
- Seamless data flow: No changes to your existing Langfuse instrumentation. Traces flow automatically to Nebuly for user intent, sentiment, and adoption analysis.
- Tag-based segmentation: Use Langfuse tags to add user context (segment, geography, cohort, role). Analyze adoption by any dimension that matters.