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Use cases

One pattern. Ten ways to prove it.

Every "show me" moment runs the same engine, from a different starting point — and lands on Reduce Risk, Reduce CAPEX, Reduce OPEX.

settlement-agentGoverned • owner a.reyes • expires with Contract C
recon-agentScope drift • sub-agent chain widened past the grant
sales-orchestratorProject closed 09 Aug • still billing $5,810

Illustrative. Governed, drifting, and billing after its project closed.

Business decisionRelationship changeLong-tail impactRisk + costActionMeasured outcome
Show me
SHOW ME #1Blast radiusTerminate a vendor — trace every contract, project, human, agent and application it touches.
SHOW ME #7The unexpected relationshipA nine-hop chain from a vendor to a board memo, surfaced in one query.
SHOW ME #8Any starting pointThe same trace from a project, a dataset or an agent — third-party risk is the wedge, not the boundary.
Reduce Risk · where it lives

Risk hides in plain sight.

None of these is a broken control. Each one is a relationship nobody owns — which is why no single system flags it.

The context each identity arrives with
7 of 15 facts missing
Supplied by idGenius
Employee
HRIS · IGA
Identity record
✓
Named owner
✓
Contract or scope
✓
Business purpose
✓
End date
✓

Joiner-mover-leaver works because every control has context to bind to.

AI agent
Stood up in code
Identity record
✓
Named owner
✗
Contract or scope
✗
Business purpose
✗
End date
✗

Spawns at runtime, inherits scope, outlives the project. No owner, no end date.

Third party
TPRM questionnaire
Identity record
✓
Named owner
✗
Contract or scope
✓
Business purpose
✗
End date
✗

A contract exists, but nothing ties it to the access the vendor actually holds.

Identity class
Identity record
Named owner
Contract or scope
Business purpose
End date
Employee
HRIS · IGA
✓
✓
✓
✓
✓
AI agent
Stood up in code
✓
✗
✗
✗
✗
Third party
TPRM questionnaire
✓
✗
✓
✗
✗

Employee —Joiner-mover-leaver works because every control has context to bind to.

AI agent —Spawns at runtime, inherits scope, outlives the project. No owner, no end date.

Third party —A contract exists, but nothing ties it to the access the vendor actually holds.

Illustrative. The control you have over an employee is the context you hold about them — idGenius supplies the same context for the identities HR never recorded.

412
Terminated contractorOffboarding left a dangling identity months after the engagement ended.Assign owner · revoke
268
Supplier account driftA vendor's machine identity drifted past what the contract allows.Right-size to contracted scope
1,087
Inherited human sessionAn assistant acting under an employee's OAuth token. The role changes; the agent keeps the old scope.Re-issue grant · expire
193
Agent-to-agent chainingAn orchestrator calls sub-agents. No single grant looks wrong; the path was never approved.Approve the composite path
57
Pre-agent contract termsA supplier's agent touches your data under language that never contemplated machine behaviour.Flag clause · renegotiate
84
Shadow agent on SaaSStood up outside review, absent from IGA and CMDB, holding live access nobody inventoried.Block or adopt into a bundle
Illustrative outcome band
Overlapping tools retired−41%IGA, TPRM, VMS and CMDB duplication identified
Integration spend closed−63%Schema on read instead of an ETL program
Agent relationships found18,204Ungoverned on first read-only discovery
With no named owner61%Each one a safe-reduction or closure candidate
Reduce CAPEX

Schema on read. No migration.

Overlap identified, duplicates retired, integration spend closed. No rip-and-replace.

Schema on readEach source keeps its native shape. New entity types resolve at query time, not at ingest.
No ETL programYears of integration work and millions of dollars — or read it where it already lives.
Overlapping governance toolsIGA, TPRM, VMS, IAM, CMDB — two systems that disagree are two you are paying for.
2,000+ integrationsIdentity platforms, applications, documents and data providers, resolved into one schema.
Reduce OPEX

Continuous governance, not campaigns.

Analysts × hours × cycles + consulting dollars — the programme cost of governing by campaign, replaced by a continuous state.

Where labour and consulting dollars go
Every quarter
Consulting dollars — IAM · IGA · VMS · TPRM · GRCProgrammes, reviews and evidence stitched together by hand, on top of the licence cost.
Access reviews and certificationsStill run manually after investing in IAM, IGA, VMS, TPRM and GRC. Every quarter, every year.
TPRM assessmentsEvery vendor answers a questionnaire, but the access context is lost once they reach your data.
Analysts × hours × cyclesThe recurring labour line that no tool purchase has removed.
Filled in with your own numbers. No invented savings.
Continuous certificationException-only deltas instead of quarterly campaigns across IAM, IGA, VMS, TPRM and GRC.
Evidence on demandAudit-ready chains already assembled — no collection exercise, no stitching by hand.
TPRM assessments answeredVendor questionnaires carry the access context they were missing, so nothing is re-gathered.
Consulting displacedThe relationship mapping consultants bill for, run in-house and read-only.

The recurring labour line no tool purchase has removed — analysts, cycles and consulting dollars, filled in with your own numbers.

The proof

Every decision carries an evidence chain.

Policy is not a PDF — it is a runtime. Every decision cites the clause it came from, so an auditor reads policy, not inference.

A
What happenedEvery governance decision carries its full attribution chain.
B
Why, and who approvedPolicy, policy version, decision timestamp, approver — cited to the source clause.
C
What enforced it — and it workedEnforcement point, enforced result, observed state, evidence.
D
What it costCost-provenance on every action: token and compute spend against the analyst hours it replaced.
Identity ledger

One immutable trail per action.

idGenius · Identity ledgerSIEM-STREAMED
  1. [14:02:01]Discovered: orchestrator agent on corporate SaaS└── Absent from IGA and CMDB
  2. [14:02:04]Owner resolved: Project B · Vendor A · Contract C
  3. [14:02:09]Policy evaluated: agent data-access v4└── Clause 4.2 cited in the decision record
  4. [14:06:33]Scope drift: sub-agent chain widened past the grant└── Composite path was never approved
  5. [14:06:35]Enforced: token scope reduced at the LLM gateway
  6. [18:40:00]Retired: project closed, standing agent still billing└── Safe-reduction candidate raised to the owner

Illustrative entries. Replayable, reconstructable, SIEM-streamed.

What the POC looks like

Read-only, on your systems, in days.

1–3 days · by complexityDiscover and learnConnectors read in place. Every actor surfaces — conflicts and policy violations visible immediately.
1–2 days · by complexityGovern and enforcePolicy published once, live, to the enforcement points you already run.
1–2 days · by complexityObserve and auditLive risk computed on your real graph. One trail per action — replayable and reconstructable.
60 minutesExecutive summaryExactly how idGenius lowers risk, CAPEX and OPEX in your environment — measured on what the first three phases found.

Standards-based. Measurable risk reduction. Measurable CAPEX and OPEX reduction.

AI token economics

Every token traced to a business purpose.

Model spend is invisible until you can name the decision that bought it — agent, project, contract, owner.

AGENT → AGENT → MODEL → TOKENS → APPLICATION → PROJECT → OWNER → CONTRACT → BUSINESS PURPOSE

Cost provenance · one action
ATTRIBUTED
Agentsales-orchestrator-agent$4,120
Sub-agentrecon-agent · 2 hops$1,870
Modelclaude-sonnet · 41.2M tokens$3,940
ApplicationRevenue workbench—
ProjectProject B · closed 09 Aug—
Ownera.reyes · Vendor A—
PurposeNo active business purpose$5,810
Illustrative. Every dollar resolves to a business purpose, or it is a reduction candidate.
Where it is invisible today— Agent-to-agent calls — no cost owner assigned.— Model spend not tied to any business decision.— Standing agents still billing after the project closes.
What idGenius adds— Cost attribution — every dollar tied to a business purpose.— Safe-reduction candidates flagged automatically.— Human vs. AI OpEx shown as two distinct lines.
$0net-new infrastructure to evaluate — idGenius reads systems already in place
1 graphin place of separate IGA, PAM, TPRM and DSPM point-tool renewals
Weeksto first value — not a multi-year integration or ETL program

Illustrative — exact CapEx offset is measured against your current tool footprint during the PoC.

Book a demo

Book a demo to understand how idGenius can lower risk, control token economics and reduce CapEx and OpEx for AI.

Read-only connections. Nothing replaced, nothing disrupted.
A discrepancy ledger — where the gaps are, what they cost, what to prioritize.
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