Summary: Reviewers can't certify access responsibly without knowing what their role peers hold — but manually cross-referencing peer access across dozens of apps is impractical. Oleria, an AI-native identity security & governance platform, solves this with continuous peer group access analysis surfaced inline on every review line, showing coverage percentage and driving an AI recommendation so reviewers stop guessing and start deciding on evidence.
See what peers in the same role have — and what reviewers should grant or revoke.
Peer-group analysis surfaces the access patterns that are normal for a role and drives the recommendation per line. Reviewers stop guessing.
Most access reviews ask the reviewer to certify entitlements one by one with no context. Did the user need this access? Compared to whom? The reviewer doesn't know — so they approve to avoid breaking work. The review completes; the access set never narrows.
Peer comparison is the obvious answer, and it's what good IGA program leads have always wanted. Doing it manually means cross-referencing thirty role-holders across twenty apps before every review cycle. Most teams give up. Oleria computes the peer comparison continuously and surfaces it inline as the input to every line's recommendation.
% Every line shows the percentage of role peers who hold the same access. Reviewers see the norm, not just the entitlement.
When peer coverage is low — the user holds access few peers have, or is missing access most peers have — Oleria's recommendation is Reject or Needs review. When peer coverage is high, the recommendation is Approve. The peer signal is one of the three inputs to every per-line recommendation.
Default groups by title + department + location. Customer-configurable per organization, per identity type
When peer coverage is high, the recommendation is straightforward — accept in bulk, focus attention on the low-coverage lines that need it.
Oleria's AI computes peer-group access continuously and presents the comparison inline. Peer coverage is one of three signals that feed the per-line recommendation — alongside Dormant Days and HR Changes. Reviewers see what's normal and the recommendation it drives, without leaving the review screen.
Reviewer time on routine lines Minutes → seconds
Low-coverage lines surfaced As recommendations, not separate flags
Access actually narrowed by review Materially up
Audit findings on review depth Eliminated
It strengthens the control — every decision shows the comparison the reviewer made it against.
Yes. Campaigns can scope to different attribute sets per organization configuration.
When peer data is sparse, the peer signal is shown as insufficient data and the reviewer falls back to usage and HR change signals.
When peer coverage is low, Oleria's recommendation is Reject or Needs review. When peer coverage is high, the recommendation is Approve.
The set of identities sharing job-attribute combinations Oleria reads from HRIS — typically title or department or location. Peer attributes are configurable per organization.
