Use Cases

Real questions. Real answers.

Skuiddy is built for the questions that matter most to enterprise leadership — the ones that require connecting data across systems, teams, and domains. Here's how it delivers for each stakeholder.

CIO CISO Enterprise Architecture AI Governance Finance Legal Operations

CIO

Chief Information Officer

Strategy, Investments, Modernization, and AI Readiness

The Challenge

CIOs are expected to lead AI transformation strategies, optimize technology investments, and rationalize legacy systems — often without a current, accurate view of what the organization actually runs. Architecture diagrams are stale. CMDBs are incomplete. AI usage is fragmented across teams and vendors.

What Skuiddy Does

Builds a continuously updated inventory of all technology assets, applications, and cloud resources
Maps AI model adoption across teams, providers, and use cases — surfacing what is in production and what is shadow AI
Identifies legacy systems, end-of-life platforms, and technology duplication
Surfaces vendor overlap and SaaS redundancy with cost context
Provides a living technology portfolio view that updates as the environment changes

Outcomes

→Complete enterprise application inventory across 22 systems — delivered in hours, not months
→AI readiness assessment identifying which data assets are AI-accessible and which governance gaps exist
→Modernization backlog automatically surfaced from discovered end-of-life and unsupported systems

Questions This Enables

"
What applications does this organization actually run?"
"
Which AI models are in production and who authorized them?"
"
Where are we paying for duplicate capabilities across vendors?"
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What does the technology portfolio look like relative to our business capabilities?"

CISO

Chief Information Security Officer

Exposure, Identity, Controls, and AI Risk

The Challenge

Security teams have more tools than ever — Wiz, CrowdStrike, Splunk, and others. But the findings from each tool lack organizational context. A critical vulnerability is meaningless without knowing what system it's in, who owns it, what data it touches, and whether there are compensating controls.

What Skuiddy Does

Enriches security findings with organizational context: owner, criticality, data sensitivity, and business impact
Maps identity posture across all providers — surfacing overprivileged accounts, orphaned service accounts, and access anomalies
Tracks AI model exposure — which models access sensitive data, which deployments are policy-violating
Provides a unified view of security posture across cloud, identity, and application layers
Connects incidents and vulnerabilities to the business capabilities they threaten

Outcomes

→Security findings enriched with ownership and business context — without manual triage or asset management overhead
→AI risk inventory showing every model, its data access, its owner, and its policy status
→Identity risk surface mapped across Okta, Entra ID, and AWS IAM in a single view

Questions This Enables

"
Which critical systems have open vulnerabilities with no assigned owner?"
"
What AI models are accessing PII or regulated datasets?"
"
Where is MFA not enforced on privileged accounts?"
"
What is the blast radius of this critical infrastructure incident?"

Enterprise Architecture

Systems, Dependencies, Lifecycle, and Technical Debt

The Challenge

Enterprise architects are responsible for understanding the current-state architecture — but that current state is almost impossible to maintain by hand. Architecture diagrams go stale the moment they're published. Dependency maps are incomplete. System ownership is tribal knowledge.

What Skuiddy Does

Continuously discovers and maps every application, service, API, and infrastructure resource
Surfaces system-to-system dependencies and integration patterns extracted from actual telemetry
Identifies redundant capabilities — multiple systems serving the same function
Flags end-of-life systems, unsupported platforms, and technical debt signals
Maintains the current-state architecture automatically, continuously, and accurately

Outcomes

→Living architecture model with real dependency graphs — replacing stale Visio diagrams
→Redundancy analysis identifying capabilities served by 2+ systems
→EOL system registry surfaced automatically without manual audit

Questions This Enables

"
What is the current-state application architecture?"
"
Which systems have the most inbound dependencies and are highest risk to change?"
"
Where are we duplicating the same business capability across multiple systems?"
"
What APIs are external-facing with no ownership or contract?"

AI Governance

AI Governance & Enablement

Model Inventory, Usage Policy, Data Risk, and Compliance

The Challenge

AI governance teams need to know what AI is running, where, on what data, by whom, and under what policy. The answer is almost always: we don't fully know. AI adoption is fast, fragmented, and often unauthorized — spread across cloud providers, SaaS tools, and business-unit experiments.

What Skuiddy Does

Automatically discovers AI models, agents, and API usage across all connected cloud and SaaS platforms
Maps which models access which data — including regulated, sensitive, or policy-controlled datasets
Tracks AI spend across providers and correlates it with teams and use cases
Enforces AI usage policies — flagging unauthorized deployments, unapproved models, and missing registrations
Maintains a continuously updated AI inventory for reporting, auditing, and board-level transparency

Outcomes

→Full AI inventory across all environments — including shadow AI detected via API usage signals
→Data-model mapping showing which models access PII, PHI, or IP-sensitive datasets
→Policy violation registry with severity, owner, and resolution status

Questions This Enables

"
What AI models is this organization using right now?"
"
Which teams deployed AI without going through the governance process?"
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What data are AI models accessing, and is any of it regulated?"
"
What is the total AI cost across providers, mapped to teams and use cases?"

Finance

Finance & IT Finance

SaaS Spend, Cloud Cost, Vendor Rationalization

The Challenge

Technology spending is often opaque: SaaS contracts managed in separate systems, cloud spend attributed to cost centers that don't reflect actual ownership, vendor overlaps invisible until someone does a manual audit. Finance teams can't optimize what they can't see.

What Skuiddy Does

Inventories every active SaaS vendor, contract, and renewal date
Correlates cloud spending with the teams and business capabilities that drive it
Identifies vendor overlap — tools providing the same capability to different parts of the org
Surfaces unused or underutilized licenses with usage data from connected platforms
Provides vendor and contract context for procurement decisions and negotiations

Outcomes

→Identified $400K in redundant SaaS licenses and overlapping vendor capabilities in a pilot engagement
→Complete SaaS vendor map with contract terms, renewal dates, and utilization signals
→Cloud cost attribution by department and business capability — not just by account tag

Questions This Enables

"
What is the total SaaS spend by department and by capability?"
"
Which tools serve identical functions across different business units?"
"
What contracts are renewing in the next 90 days and should we renegotiate?"
"
Which licenses are we paying for that are barely being used?"

Legal

Legal & Compliance

Contracts, Data, Policies, and Regulatory Obligations

The Challenge

Legal and compliance teams are asked questions that require understanding of both the organizational structure and the technical reality — who processes personal data, which systems are in scope for a regulation, which vendors have access to regulated information. Answering these manually takes weeks and is almost always incomplete.

What Skuiddy Does

Maps all systems and vendors that process personal, health, or financial data
Identifies regulatory scope across GDPR, HIPAA, PCI-DSS, SOC 2, and other frameworks
Maintains a data flow map showing which systems transfer data to which vendors across jurisdictions
Provides contract and DPA status for all active vendors
Supports subject access requests and regulatory inquiry response with structured entity context

Outcomes

→Regulatory scope map for GDPR, HIPAA, and PCI-DSS completed in days, not months
→Subject access requests handled with a structured entity query rather than a manual email chain
→Vendor data processing map with DPA status and jurisdiction classification

Questions This Enables

"
Which vendors and systems process personal data, and under what agreement?"
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Which systems are in scope for our HIPAA or PCI-DSS compliance program?"
"
What data flows cross jurisdictional or regulatory boundaries?"
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Which systems and vendors are relevant to this subject access request?"

Operations

Operations & Platform Engineering

Incident Context, Ownership, and Operational Intelligence

The Challenge

When an incident occurs, the first challenge is not fixing it — it's understanding what is affected, who owns it, what changed recently, and what the blast radius is. That context is scattered across a dozen tools, and assembling it wastes critical response time.

What Skuiddy Does

Provides immediate organizational context for any incident: affected systems, owners, dependencies, and data impact
Surfaces recent changes to the affected systems — configuration changes, deployments, access changes
Maps ownership for every service, API, and infrastructure resource discovered by sensors
Identifies unowned or ungoverned systems before they become a problem
Connects operational signals to the business capabilities they affect

Outcomes

→Incident context assembly reduced from 45 minutes to under 5 minutes with Twin-enriched data
→Unowned service registry surfaced automatically — no manual audit required
→Change blast radius assessment available for any system change through the Twin graph

Questions This Enables

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What systems are affected by this incident, and who owns each one?"
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What changed in the last 24 hours that could explain this failure?"
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Which services have no on-call owner assigned?"
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What is the full dependency chain for this critical service?"

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