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How to Configure Platform Settings

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TL;DR
Settings → Platform Settings is the single place for instance-wide configuration: upload limits, login and SSO methods, branding, data source connectors, governance rules, default reports, and the AI assistant. Pick a section on the left, click Edit, make your change, then Save.

Controls uploads and script validation.

  • Maximum File Size - the largest file, in MB, a user can upload.
  • Allowed File Extensions - a comma-separated list with leading dots (for example, .csv, .xlsx, .pdf). Only these types can be uploaded.
  • Allowed Python Imports - the modules users may import in object definitions and scripts. Checked when the platform validates definition syntax.
  • Allow file upload as Input Source in Table Registry - toggle. Lets users register tables directly from an uploaded file.
  • Enable UI Telemetry (OpenTelemetry) - toggle. Turns on UI tracing. To send traces and metrics to Grafana, set TELEMETRY_OTLP_ENDPOINT in corridor-app settings and restart the server.

Sets how users sign in.

  • Allowed Login Options - multi-select of Password, Email OTP, Enterprise SSO, Google, and Microsoft. At least one is required.
  • Whitelisted Domains - comma-separated email domains allowed to sign in through a federated method (Google, Microsoft, or Enterprise SSO). Leave blank to allow any domain.
  • Default Role - the role assigned to a user provisioned on their first SSO login.

Whitelisted Domains and Default Role appear only once a federated login is enabled.

All fields optional.

  • Financial Institution Type - Credit Union or Bank.
  • Brand Name - the name shown in the product.
  • Primary Logo - logo for light backgrounds (SVG or PNG).
  • Reverse Logo - logo for dark backgrounds (SVG or PNG).
  • Data Lake - Pre Read Hook - Python that runs before the platform reads from a Data Lake source, for example to inject connection options like Snowflake credentials. The hook can use the location and username variables. Leave blank for no hook.

Spark connector options for each data source type: Snowflake, MSSQL, Oracle, Hive, and Other JDBC. Click a source’s gear icon to set its options. A configured source shows an Active badge.

  • Require Supporting Analysis for approvals and reviews - toggle. When on, every approval and review must have a job attached as supporting analysis.
  • Roles with Retire Permission - the roles allowed to use Retire on workflowable objects.

For each simulatable object type, pick the reports selected by default when a simulation runs on it. Object types: Quality Profile, Data Element, Feature, Model, Dataset, and Policy.

Define display formats keyed by Alias. Each row pairs a unique Alias with a Format (0, 0.00, 0.000, 0.0000, 0%, or 0.00%), which controls how that value renders in Single Record Review output.

Two sub-tabs configure the platform assistant.

Sets the assistant’s provider and model.

  • Provider - Azure OpenAI, OpenAI, Anthropic, Google, AWS Bedrock, or Google Vertex AI.
  • AI Bot Name - display name for the assistant (for example, CORRA).
  • Authentication - fields change with the provider: an API key for most, AWS region and access keys for Bedrock, GCP project and location for Vertex AI, plus endpoint and API version for Azure OpenAI. Saved keys are masked; use Change key to replace one.
  • Model Name - the model to use (labeled Deployment Name for Azure).
  • Temperature - 0 to 2 (default 0.7).
  • Max Tokens - 1 to 128000 (default 4096).
  • Enable streaming responses - toggle, off by default. Streams the assistant’s reply word by word as it generates, instead of showing it all at once when finished.

Wires up Langfuse tracing.

  • Enable Langfuse Tracing - toggle.
  • Public Key - your Langfuse public key (pk-...).
  • Secret Key - your Langfuse secret key (sk-...); masked once saved, use Change key to rotate.
  • Host - optional; defaults to https://cloud.langfuse.com.