AI control plane for enterprise finance transactions

Trace every revenue transaction. Explain every exception. Govern every AI action.

NexLedger connects CRM, ERP, billing, RMCS, AR, GL, and audit evidence without replacing your existing systems. Finance teams see where revenue breaks, why it matters, and which policy controls the next step.

Get a Revenue Leakage Assessment View Architecture
Trace
Source to journal lineage
Inspect
Policy gates and materiality
Prove
Audit evidence by design

Finance teams do not have a data problem. They have a transaction truth problem.

Revenue teams can see records in each application. What they cannot see is the governed path from quote to journal, including where policy was inspected and what evidence proves the decision.

01

Leakage hides between systems

Discounts, order changes, usage events, invoices, revenue schedules, and cash application drift apart before anyone owns the whole transaction.

02

Close exceptions arrive late

Controllers discover mismatches after data has already moved through billing, RMCS, AR, and GL. The root cause investigation starts when time is gone.

03

Evidence is rebuilt after the fact

Audit support still depends on screenshots, spreadsheets, ticket notes, and people remembering why a decision was made.

One governed layer across your finance systems.

NexLedger turns fragmented source activity into a transaction graph that finance, systems, AI, and audit teams can all rely on.

Transaction Graph

Resolves source records into one quote-to-cash-to-journal lineage, with every edge tied to system, field, policy, actor, and timestamp.

Policy Runtime

Evaluates pricing, revenue, materiality, approval, and evidence requirements before recommendations move forward.

AI Reasoning Layer

Lets AI investigate exceptions with governed context, then explains the cause, impact, policy basis, and next action.

Evidence & Audit Layer

Creates replayable evidence packages with source lineage, decisions, approvals, controls, timestamps, and hashes.

Built for revenue, close, controls, and audit.

Each module uses the same governed transaction layer. The work changes by team, but the evidence stays connected.

TransactionDNA

Maps quote-to-cash-to-journal lineage and detects breaks across systems.

Lineage coverage across Salesforce, CPQ, Order, Billing, RMCS, AR, GL, and audit evidence.

Revenue Close Agent

Investigates exceptions, prioritizes material risk, and prepares close-ready explanations.

Exception queues ranked by financial exposure, close impact, and evidence sufficiency.

AI Control Plane

Ensures AI agents can investigate and recommend, but cannot bypass finance policy.

Policy-bound permissions, approval gates, segregation of duties, and decision replay.

Evidence Manifest

Creates audit-ready evidence packages with lineage, decisions, controls, and timestamps.

Cryptographic hashes connect source records, policy checks, actor identity, and approvals.

Use cases mapped to the people who own the risk.

NexLedger is designed around the questions each finance stakeholder must answer before close, audit, transformation, and AI adoption.

Controller / Revenue Accounting

  • Revenue exception management
  • Close readiness
  • RMCS reconciliation

Audit / SOX

  • Evidence automation
  • Control testing support
  • Decision replay

CIO / Finance Systems

  • Cross-system lineage
  • Integration visibility
  • AI governance

CFO / Transformation

  • Revenue leakage visibility
  • Finance AI readiness
  • Operating model modernization

Architecture that preserves the systems you already run.

NexLedger sits above source systems as a governed intelligence layer. It correlates records, evaluates policy, explains exceptions, and writes the audit trail.

Source systems

Salesforce Oracle OM Billing RMCS AR GL

NexLedger layers

  1. 01 Ingestion
  2. 02 Canonical Transaction Model
  3. 03 Transaction Graph
  4. 04 Policy Runtime
  5. 05 AI Reasoning
  6. 06 Evidence Store
  7. 07 Workbench

Finance outputs

Exceptions Evidence Approvals Close readiness Audit trail

Designed for enterprise finance controls.

The product model assumes segregation of duties, human review, evidence retention, and skeptical auditors from day one.

Role-based access Human approval gates Policy-bound AI Audit trail Tenant isolation No rip-and-replace Evidence retention Private deployment options

Revenue leakage assessment

Find where revenue leakage and close risk hide in your systems.

We map your quote-to-cash-to-journal flow, identify control gaps, and show where NexLedger can create transaction-level visibility.

Request Assessment Talk to NexLedger