Your preferred date ranges now persist between sessions, with preset options like "Last 7 days" available for faster reporting. 

Date filters automatically apply when you reopen the app.

Launched flexible date range selection with period-over-period comparison, allowing teams to analyze trends across any custom time-frame instead of fixed periods.

Added ranking movement indicators (↑↓) to show how customer interaction categories change in importance over time, helping teams quickly spot and communicate emerging patterns.

We're upgrading our AI engine to Claude 3.5 for enhanced accuracy and reliability in your AI agent insights. This brings significant improvements to our core analysis capabilities.

Claude 3.5 is now available for customers using Snowflake in the Oregon region. For other regions, you can enable Cross-region inference in your Snowflake account to access Claude 3.5 (see docs).

We've added timezone configuration to help global teams work with their data more accurately. Your AI agents will now correctly interpret dates across different timezones.

The new timezone settings include automatic detection from your data and manual override options when needed. This eliminates date discrepancies when analyzing data across different regions.

Configure your timezone in your agent's settings.

We're introducing the ability to create custom AI agents that adapt to your specific use cases. This is a major step forward in making our AI analysis more flexible and valuable for your unique business needs.

Custom agents let you define exactly what you want to discover from your data, while maintaining the same powerful integration with your Snowflake data. Select your data source and define your discovery goals. The preview will show you example insights before you launch your custom agent.

Custom agents are now available in beta.

We've redesigned the agent creation flow to make it easier to get started and more transparent about what you'll discover. These improvements help reduce setup time and ensure you get valuable insights from day one.

The new setup experience includes clearer error messages with step-by-step resolution instructions, particularly around Snowflake permissions. You'll see exactly what access is needed and how to enable it.

We've also added an insights preview that shows examples of what your agent might discover based on your industry and use case. This helps set clear expectations before you launch the agent.

Automatically discover important trends and patterns in your customer data with our new Highlights feature. This update surfaces significant changes across your insights and metadata dimensions, helping teams quickly identify emerging patterns without manual analysis. Stay proactive with period-over-period comparisons that bring attention to what matters most.

We recently launched our new website that showcases how our AI Agents analyze your Snowflake data to turn customer interactions, product usage, and revenue data into actionable insights that drive growth – all while keeping your data secure in your Snowflake environment

Learn more at our website: lang.ai

This update is another step towards bringing our users more transparency on how Lang works. In a nutshell, hovering on a tag in the Search view will highlight the piece of text that is relevant for the tag.