Find
Search and filter across metadata and source.
Evidence was trapped inside individual workflows
Every stage of the third-party risk lifecycle produced files. Because those documents remained tied to the activity that generated them, retrieving evidence depended on knowing where it had entered the platform. The repository created a persistent layer across those workflows.
Onboarding→Due diligence→Assessment→Monitoring→Offboarding
↘ ↓ ↓ ↓ ↙
Persistent evidence layer across the TPRM lifecycle
Define the repository around evidence jobs
I translated the fragmented-document problem into four durable jobs. These became the product model for deciding what belonged in the repository and how the experience should be structured.
Understand
Use metadata and contextual preview before opening a file.
Trace
Preserve source, activity and history.
Manage
Maintain category and expiry, then act on documents individually or in bulk.
Make documents usable as evidence
Three decisions turned the repository from a file library into an operational evidence product.
Preserve provenance, not just the file
Source Type remained a first-class concept so users could understand where evidence entered the platform and filter by that context.
Reduce the need to open every document
The repository and preview exposed useful metadata so common questions could be answered before opening the source file.
Ship useful metadata before automating it
Manual category and expiry management created immediate value while keeping a clear path to automated classification and extraction.
One repository across the TPRM lifecycle
I owned the product decisions end to end across two production releases, aligned engineering, design and implementation stakeholders, and led the rollout enablements. The product progressed from a shared foundation to a richer operational experience.
Centralize
Established the shared repository, search, filtering and source context across the platform.
Operate
Expanded preview, activity, history and document management using implementation and UAT feedback.
SearchFilteringMetadataSource contextPreviewActivity & historyDocument managementBulk download
From evidence storage to document intelligence
Once the persistent evidence layer existed, I defined how the repository could progress from storing documents to understanding their contents and making the right evidence reusable in AI-assisted workflows.
Centralize
Bring evidence from across the lifecycle into one persistent layer.
Find & manage
Search, trace, preview and maintain documents without returning to the source workflow.
Classify & reuse
Extract useful facts, surface document meaning and make evidence available to AI workflows.
Product outcome: a shared evidence layer released to production, a durable model for working with third-party documents and a defined path toward document intelligence.