Prodigy - OpenText Identity and Access Management Integration and Automation

Common Integration Use Cases Between Prodigy and OpenText Identity and Access Management

1. Secure, role-based access to annotation projects

Data flow: OpenText Identity and Access Management ? Prodigy

Use OpenText Identity and Access Management to authenticate annotators, reviewers, and ML engineers through single sign-on and assign access based on role. Prodigy projects can be restricted so that only approved users can view sensitive datasets, create labels, or approve annotations. This is especially valuable for regulated industries handling customer records, medical images, or confidential legal text.

Business value: Reduces manual user administration, improves auditability, and ensures only authorized staff can access training data.

2. Automated onboarding and offboarding for data labeling teams

Data flow: OpenText Identity and Access Management ? Prodigy

When new annotators, contractors, or subject matter experts join a project, their access to Prodigy can be provisioned automatically based on identity and group membership in OpenText Identity and Access Management. When they leave or change roles, access can be revoked immediately. This prevents orphaned accounts and reduces the risk of unauthorized access to active training datasets.

Business value: Speeds up project start times, lowers IT support effort, and strengthens security controls across fast-moving AI teams.

3. Segregation of duties between annotators, reviewers, and administrators

Data flow: Bi-directional

OpenText Identity and Access Management can enforce distinct access policies for different Prodigy user groups. Annotators may only label data, reviewers may approve or reject labels, and administrators may manage workflows and dataset access. Prodigy activity can be tied back to identity records for accountability and compliance reporting.

Business value: Improves quality control, supports governance requirements, and reduces the risk of one user performing conflicting tasks in the same workflow.

4. Controlled access to sensitive training data across business units

Data flow: OpenText Identity and Access Management ? Prodigy

Organizations often use Prodigy to label data from multiple departments such as HR, legal, customer service, or manufacturing. OpenText Identity and Access Management can enforce business-unit level access so each team only sees the datasets assigned to them. This is useful when different teams are building separate models from different confidential data sources.

Business value: Prevents data leakage between departments, supports internal data governance, and enables broader AI adoption without compromising confidentiality.

5. Audit-ready annotation activity tracking for compliance teams

Data flow: Prodigy ? OpenText Identity and Access Management

Prodigy user actions such as login events, project access, and annotation changes can be linked to identity records managed in OpenText Identity and Access Management. Compliance teams can then trace who accessed which dataset, when labels were changed, and which user approved the final training set. This is important for industries that need evidence of controlled data handling.

Business value: Simplifies audits, strengthens traceability, and supports internal and external compliance reviews.

6. Secure collaboration with external labeling vendors or domain experts

Data flow: OpenText Identity and Access Management ? Prodigy

Many enterprises use external specialists to label niche datasets such as radiology images, insurance claims, or technical support transcripts. OpenText Identity and Access Management can provide controlled access for external users through federated identity or managed accounts, limiting them to only the Prodigy projects they need. Access can be time-bound and automatically removed when the engagement ends.

Business value: Enables flexible workforce scaling while maintaining strong security boundaries and reducing vendor access risk.

7. Centralized access policy enforcement for AI development environments

Data flow: OpenText Identity and Access Management ? Prodigy

Enterprises often connect Prodigy to broader AI development workflows that include data stores, notebooks, and model training systems. OpenText Identity and Access Management can act as the central identity layer for these environments, ensuring that only users with the correct entitlement can move from raw data access into annotation work and then into downstream model development. This creates a consistent access model across the AI lifecycle.

Business value: Reduces policy gaps between systems, improves operational consistency, and supports end-to-end governance for machine learning programs.