Nexoraa replaces manual matching and exception triage with multi-agent workflows that ingest statements, match transactions, identify breaks, propose corrections, and route only the genuine exceptions to a human - with full audit trail.
Reconciliation is one of the most expensive recurring operations in any large enterprise. Statements arrive in inconsistent formats from dozens of counterparties. Matching rules change constantly. Exceptions stack up. Period close slips. Auditors raise findings. Most teams fall back on spreadsheets, ad-hoc scripts, and a small number of tenured staff who hold the institutional knowledge in their heads.
Inconsistent input formats
PDF statements, CSV exports, swift messages, and ERP extracts arrive in different formats from different counterparties, none stable over time.
Brittle rule-based matching
Static rule engines miss legitimate matches and surface false breaks; tuning rules introduces silent regressions elsewhere.
Exception backlog
Thousands of breaks per day mean analysts spend more time triaging than resolving; period close slips.
Lost institutional knowledge
Resolution logic lives in the heads of senior staff; when they leave, accuracy degrades.
Audit pressure
Auditors want evidence of every match decision and every exception treatment.
Nexoraa decomposes reconciliation into a multi-agent pipeline. Each agent has a single responsibility, a defined output schema, and a validation gate. Human approval is required only where policy specifies it.
- 1
Ingestion Agent
Accepts statements in supported formats and normalises every record into a validated JSON schema.
- 2
Matching Agent
Applies rule-based logic for structured fields and semantic matching for fuzzy fields, returning high-confidence matches with cited reasoning.
- 3
Break Identification Agent
Classifies unmatched records as timing, FX, fee, mis-booking, or true breaks and writes rationale into the audit trail.
- 4
Resolution Proposer Agent
Proposes a resolution drawn from prior cases, memory, and deterministic policy rules.
- 5
Haluvance Validation
Validates each output against schema, confidence threshold, and policy before promotion.
- 6
Human-in-the-Loop
Routes material or low-confidence items to a queue with context, evidence, and the agent's proposal.
- 7
Posting Agent
Posts approved entries to the ERP, captures the journal ID, and closes the break in the audit trail.
Nexoraa
Governed connectors
13
systems named here
- SAP
- Oracle ERP
- Workday
- Microsoft Dynamics
- NetSuite
- custom GL systems
- banking partners
- SWIFT
- ISO 20022
- host-to-host feeds
- SharePoint
- Box
- S3
Exception volume
↓ LowerFewer items reach a human queue because policy-resolvable cases are auto-resolved.
Time to close
↓ LowerPeriod close compresses because matching, classification, and posting run continuously.
Audit posture
↑ HigherEvery match, classification, and treatment carries a citation and stored rationale.
Knowledge retention
↑ HigherEpisodic memory captures resolution patterns so turnover stops degrading accuracy.
Governance
↑ HigherPosting actions sit behind policy gates and approval workflows.
2 controls, applied to every run
Nexoraa enforces role-based tool governance, deterministic policy gates, full lineage from statement line to journal entry, and Haluvance enforcement on every agent action
The complete execution trace is retained per the customer's compliance policy
- Multi-format ingestion
- Production-grade extraction across PDF, structured, scanned, and message-based formats.
- Deterministic + intelligent
- Rule logic is deterministic where regulators demand it; agentic where judgement helps.
- Recoverable execution
- Checkpoint and resume mean downstream failures do not require starting from scratch.
- Full traceability
- Every match cites records, every break cites reasoning, every approval logs operator identity.
Bring a sample dataset under NDA. We will demonstrate the workflow on it.