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Assist Analyzes Your Study Data

Catalyst Assist can now answer questions about the data in your study — counts, averages, distributions, and filtered breakdowns — by querying the dataset directly.

What's included

Catalyst Assist answering a data question with figures and a table

  • Ask data questions in natural language — "average overlay error by tool?", "how many wafers failed process control?", "distribution of risk score by lot" — and Assist queries your study dataset to answer
  • Answers are computed from your actual data, returned as markdown tables, with a brief takeaway drawn from the results
  • Date and duration math is supported — group by year, compare timestamps, measure elapsed time between events
  • Platform and feature questions still work exactly as before — Assist picks the right mode for each question

Notes

  • Data answers come only from your dataset — Assist never invents, estimates, or extrapolates figures
  • Data questions are available when Assist is opened from within a study
  • Data queries run on the study's worker, so it must be provisioned and active; otherwise Assist still answers platform and feature questions but can't query the dataset
  • AI responses may not always be accurate. If you receive an unexpected result, let us know with the thumbs up/down on the response, or share it via Support → Contact Support
  • This is an incremental update during beta

Improved Folder Picker

The folder picker is now easier to navigate, supports deeper search drill-down, and lets you create folders in the right place.

What’s included

Easier folder navigation

Search folder navigation Search folder navigation creation

  • You can now drill into folders directly from search results instead of starting over in the main tree
  • Search breadcrumbs stay clickable, so it’s easier to move back up when you’ve drilled in
  • Search results only show folders you can actually use, so there’s less dead-end clicking

Folder creation in the right place

Folder creation

  • The picker follows the same folder structure used in Foundry: space -> project -> folders
  • A space is like a shared drive, and its first-level listings are project resources
  • Admins manage projects, so you can browse into them but cannot create new folders at the project level itself
  • You can create folders once you’re inside the folders within a project, including after drilling in from search

Notes

  • Folder creation is only available once you’ve drilled into a valid folder location inside a project
  • If a folder does not appear in search, you may not have permission to use it

Catalyst Assist

Ask questions about Catalyst and get instant, documentation-backed answers — right from the sidebar.

What's included

Catalyst Assist panel open alongside the dashboard

  • Click Assist in the sidebar to open the panel from any page
  • Ask a question and receive a focused, markdown-formatted answer grounded in Catalyst documentation
  • Source excerpts are shown beneath each reply so you can verify or explore further
  • Follow-up questions are supported — prior context is carried forward within the same conversation
  • Use the + button to start a new conversation at any time

Notes

  • Answers are based solely on Catalyst documentation — the assistant will not speculate or invent features
  • AI responses may not always be accurate. When in doubt, refer to the official documentation for authoritative guidance
  • If you receive an unexpected or unhelpful response, please share it via Support → Contact Support
  • Conversations are limited to 20 messages; start a new one for unrelated topics

Sigma-Based PCA Clusters

Create PCA clusters from sigma bands and compare only clusters that contain points.

What's included

Create clusters from sigma bands

Sigma-based PCA clusters

  • Open the cluster menu in PCA -> Cluster Analysis to create ready-made Inside nσ and Outside nσ clusters without drawing a brush
  • Sigma-based clusters automatically assign matching points as soon as the PCA view finishes loading
  • The matching sigma contour adopts the cluster color so you can see the selected boundary at a glance

Compare populated clusters only

  • Cluster comparison menus now show only clusters that currently contain points
  • If a selected cluster becomes empty or is removed, the comparison updates to the next valid populated cluster automatically

Notes

  • Sigma-based clusters are stored with your other PCA cluster selections for that study
  • Outside nσ options are available for every displayed sigma band, while Inside nσ options are available for the inner bands
  • Empty clusters are excluded from comparison choices until they contain points

Contact Support

Send feedback, bug reports, and feature requests directly from the Support menu.

What's included

Contact Support from anywhere

Contact Support dialog

  • Open Support -> Contact Support from the app sidebar without leaving your current page
  • Submit one of three request types: General Feedback, Bug Report, or Feature Request

Faster issue triage

  • Add a clear title and detailed description so the team can understand your request faster
  • Your submission includes your current page, browser, and account details to reduce back-and-forth

Notes

  • The form requires both a title and description before you can submit
  • Messages are limited to 1,500 characters
  • For bug reports, include steps to reproduce and what you expected to happen

Exclude Columns in Data Health & Column Settings

Excluded columns are now hidden by default in the Data Health summary, and both the Data Health and Column Settings pages show a consistent "Hide excluded (N)" filter.

What's included

Standardized "Exclude" action

Summary

The action previously labeled Drop column in the Data Health table is now labeled Exclude, consistent with the terminology used in Column Settings. Excluded columns (visibility offs) are now hidden by default in the Data Health summary table. A Hide excluded (N) checkbox appears in the toolbar whenever there are excluded columns, allowing you to reveal them when needed.

Consistent filter in Column Settings

Column Edit

The same Hide excluded (N) checkbox — showing the count of excluded columns — is now displayed in the Column Settings page, matching the behaviour in Data Health.


Notes

  • Excluded columns are hidden, not deleted — your underlying data remains unchanged
  • The count in the checkbox reflects how many columns currently have visibility turned off
  • If you notice any unexpected behavior, please share steps to reproduce

AI Summary for Plot Builder

Instantly understand any plot with an AI-generated summary — powered by an LLM with vision.

What's included

How it works

AI Summary popover on a scatter plot

  • Click the AI Summary button in the Plot Builder toolbar
  • A vision-enabled LLM reads the plot statistics and sees the chart, then returns bullet points covering distributions, group breakdowns, data quality issues, and visual patterns like clusters or outliers
  • Hit copy to paste the summary into a report or analysis note

Notes

  • Works with scatter plots, box plots, and heatmaps
  • The summary is factual only — the LLM does not assess or make recommendations
  • If you notice any unexpected behavior, please share steps to reproduce

Column Management

Rename and include or exclude columns across your study from Column Management.

What's included

Column Management

Column Management

You can now manage columns from Edit → Columns.

  • Exclude columns to remove them from all views in the study — including plots, statistics, and column groups
  • Include columns again at any time to restore them across the study

Update Column

Drawer to update

  • Rename columns to use more meaningful display names across your study
  • Changes are applied consistently across all views

Notes

  • Excluded columns are hidden, not deleted — your underlying data remains unchanged
  • Renaming affects display only and does not modify raw data
  • If you notice any unexpected behavior, please share steps to reproduce

Desirability Convergence Chart

New desirability convergence chart for tracking optimization progress across experiment trials.

What's included

How it works

Numerical Parameter - select parameter

  • Select a numerical parameter from the parameter sidebar to color data points by that parameter's value
  • A continuous color scale shows how parameter values relate to desirability scores across trials
  • The best so far line tracks the highest desirability achieved up to each trial

Categorical Parameter - select parameter

  • Select a categorical parameter to color data points by category
  • A discrete color legend identifies each category value

Notes

  • The convergence chart is available under the Desirability tab in the Visualization section
  • Chart interactions and layout may continue to evolve during the beta phase
  • If you notice any unexpected behavior, please share steps to reproduce

Trellis plots in Experiment Visualization Convergence

Split convergence plot into a multi-panel grid when multiple targets are selected.

What's included

How it works

Trellis convergence plot

  • Select multiple targets from the target sidebar
  • The convergence plot automatically splits into a grid — one panel per target
  • Each panel shares the same x-axis (iteration index) but has an independent y-axis scale

Trellis - select point

  • Click a data point to highlight the corresponding trial across all panels

Trellis - draw point

  • Shift-drag to draw a brush selection across panels
  • Points outside the selection are dimmed
  • Up to 6 targets can be displayed at a time

Notes

  • Single target selection continues to show the standard convergence plot
  • Trellis layout and interactions may continue to evolve during the beta phase
  • If you notice any unexpected behavior, please share steps to reproduce