Does Nexus replace any of these systems?

No. Each system keeps its own records. Nexus runs the process between them and records each decision.

Does an outlier mean the source record is incorrect?

No; a legitimate new product, business event or entity can differ from historical patterns, so the owner reviews the evidence.

Can the model fill a missing value from what is statistically common?

Not as an authoritative correction; the owner needs an approved source or an explicitly authorized treatment, and the proposal remains separate until then.

Enterprise use case · SAP + Snowflake + OpenAI + ServiceNow

Data quality exception review

Rules catch known data defects, but unfamiliar combinations and inconsistent descriptions still reach reports without a clear investigation path. Data owners receive source-linked anomaly findings and proposed corrections without automatic changes to authoritative records.

Discuss this use case Enterprise overview

Systems involved

What each system contributes

SAP

97 actions

Core SAP7
Finance20

Snowflake

35 actions

Tables6
Views6
Data Loading & Stages8

OpenAI

25 actions

Chat Completions8

ServiceNow

55 actions

Tickets10

Trigger source: ServiceNow

The model step runs against the AI provider you choose, including Anthropic, Google Gemini or a model you host yourself. Anything outside a pre-built action runs through an API, protocol or database call, or as Rules + Code in Python, Bash, Go, Java, .NET, PHP, PowerShell or JavaScript/TypeScript, with the same approvals and audit.

Architecture

One governed run

Trigger: load completion / scheduleIntegration: SAP + SnowflakeRules + CodeAI step: model of your choiceSystem Action: ServiceNowHuman ApprovalAudit

How it starts: An SAP-to-Snowflake load or a designated dataset is released for a data-quality review.

Step by step

How the process runs

01
Establish the comparison scope
Read the authorized SAP source references and corresponding Snowflake records for the approved dataset and period.
02
Check known constraints
Rules test required fields, keys, formats and the agreed source-to-target reconciliation conditions.
03
Identify unusual records
The selected model evaluates the remaining records for atypical combinations and explains which attributes differ from the relevant comparison set.
04
Propose a correction
The model identifies a possible field-level issue with supporting references, distinguishing a candidate fix from a verified source value.
05
Route and resolve
Create a restricted ServiceNow review item and apply a correction through a separate SAP or Snowflake step only after the designated data owner approves it.

Control

Human decision and exception path

Human decision

The named data owner decides whether the source, warehouse transformation or neither should change. Any correction touching a posted SAP document requires the authorized finance approval and its permitted adjustment process before execution.

Exception path

A rare but legitimate record can be accepted with a reason rather than normalized into the majority pattern.
Missing source evidence blocks a proposed replacement value and requests clarification from the owning team.
Changed source versions or incomplete loads require revalidation before a reviewed correction is applied.

Evidence

What gets audited

SAP and Snowflake record references and comparison scope.
Constraint results, model finding and proposed field-level change.
ServiceNow review history, owner decision and approval.
Authorized correction request, response and follow-up validation.

Nexus runs on premises, in private or sovereign cloud, or air-gapped. Credentials stay in the vault, roles decide who can approve, and the execution record stays inside your deployment boundary.

Sovereignty and deployment

Snowflake-SAP integration
Integration pattern · SAP data reaches Snowflake as validated, repeatable loads with a record of completeness.
SAP connector
97 pre-built actions
Snowflake connector
35 pre-built actions
OpenAI connector
25 pre-built actions
ServiceNow connector
55 pre-built actions
Compliance evidence
Evidence produced by the work itself.
Order to cash across CRM, ERP and billing
Another enterprise use case.

FAQ

Questions about this use case

Does Nexus replace any of these systems?: No. Each system keeps its own records. Nexus runs the process between them and records each decision.
How does the run start?: An SAP-to-Snowflake load or a designated dataset is released for a data-quality review.
What if a step is not covered by a pre-built action?: The model step runs against the AI provider you choose, including Anthropic, Google Gemini or a model you host yourself. Anything outside a pre-built action runs through an API, protocol or database call, or as Rules + Code in Python, Bash, Go, Java, .NET, PHP, PowerShell or JavaScript/TypeScript, with the same approvals and audit.
Does an outlier mean the source record is incorrect?: No; a legitimate new product, business event or entity can differ from historical patterns, so the owner reviews the evidence.
Can the model fill a missing value from what is statistically common?: Not as an authoritative correction; the owner needs an approved source or an explicitly authorized treatment, and the proposal remains separate until then.

Use case review

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Bring your version of the process. We will map the systems, approvals and evidence it needs.

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