ResilNext This workflow corresponds to n8n.io template #14276 — we link there as the canonical source.
This workflow follows the Agent → Google Sheets recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"nodes": [
{
"id": "42217665-1184-40a8-bddf-b40f9e84fce1",
"name": "Webhook - Receive Financial Data",
"type": "n8n-nodes-base.webhook",
"position": [
-768,
288
],
"parameters": {
"path": "financial-data-reconciliation",
"options": {},
"httpMethod": "POST",
"responseMode": "lastNode"
},
"typeVersion": 2.1
},
{
"id": "de790021-1521-4926-bd1a-b40ae43e2794",
"name": "Workflow Configuration",
"type": "n8n-nodes-base.set",
"position": [
-592,
288
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "confidenceThreshold",
"type": "number",
"value": 0.85
},
{
"id": "id-2",
"name": "matchingKeys",
"type": "array",
"value": "[\"transactionId\", \"invoiceNumber\", \"amount\", \"date\"]"
},
{
"id": "id-3",
"name": "fuzzyMatchThreshold",
"type": "number",
"value": 0.7
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "9f455d80-262a-4af3-85ed-143db95c4696",
"name": "Check Data Source Type",
"type": "n8n-nodes-base.if",
"position": [
-368,
288
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 3,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "id-1",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.sourceType }}",
"rightValue": "bank_statement"
}
]
}
},
"typeVersion": 2.3
},
{
"id": "3beba561-8803-4b92-b81e-d5aea0832d57",
"name": "Extract CSV Data",
"type": "n8n-nodes-base.extractFromFile",
"position": [
16,
48
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "5fd65063-4ddc-441b-97b3-9f75d88c32a2",
"name": "Normalize Bank Statement Schema",
"type": "n8n-nodes-base.set",
"position": [
16,
224
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "recordId",
"type": "string",
"value": "={{ $json.transaction_id }}"
},
{
"id": "id-2",
"name": "amount",
"type": "number",
"value": "={{ $json.transaction_amount }}"
},
{
"id": "id-3",
"name": "date",
"type": "string",
"value": "={{ $json.transaction_date }}"
},
{
"id": "id-4",
"name": "description",
"type": "string",
"value": "={{ $json.transaction_description }}"
},
{
"id": "id-5",
"name": "sourceType",
"type": "string",
"value": "bank_statement"
},
{
"id": "id-6",
"name": "normalizedAt",
"type": "string",
"value": "={{ $now.toISO() }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "cd62e763-8cd1-46bb-82b6-f18078412dfb",
"name": "Normalize Invoice Schema",
"type": "n8n-nodes-base.set",
"position": [
16,
400
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "recordId",
"type": "string",
"value": "={{ $json.invoice_number }}"
},
{
"id": "id-2",
"name": "amount",
"type": "number",
"value": "={{ $json.invoice_total }}"
},
{
"id": "id-3",
"name": "date",
"type": "string",
"value": "={{ $json.invoice_date }}"
},
{
"id": "id-4",
"name": "description",
"type": "string",
"value": "={{ $json.invoice_description }}"
},
{
"id": "id-5",
"name": "sourceType",
"type": "string",
"value": "invoice"
},
{
"id": "id-6",
"name": "normalizedAt",
"type": "string",
"value": "={{ $now.toISO() }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "0efc2451-3c62-4988-85d6-e06312afa34c",
"name": "Normalize ERP Schema",
"type": "n8n-nodes-base.set",
"position": [
16,
608
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "recordId",
"type": "string",
"value": "={{ $json.erp_transaction_id }}"
},
{
"id": "id-2",
"name": "amount",
"type": "number",
"value": "={{ $json.erp_amount }}"
},
{
"id": "id-3",
"name": "date",
"type": "string",
"value": "={{ $json.erp_date }}"
},
{
"id": "id-4",
"name": "description",
"type": "string",
"value": "={{ $json.erp_description }}"
},
{
"id": "id-5",
"name": "sourceType",
"type": "string",
"value": "erp"
},
{
"id": "id-6",
"name": "normalizedAt",
"type": "string",
"value": "={{ $now.toISO() }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "0c4e99b7-8eda-4216-aba0-c14e076285c5",
"name": "Normalize CSV Schema",
"type": "n8n-nodes-base.set",
"position": [
224,
48
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "recordId",
"type": "string",
"value": "={{ $json.id }}"
},
{
"id": "id-2",
"name": "amount",
"type": "number",
"value": "={{ $json.amount }}"
},
{
"id": "id-3",
"name": "date",
"type": "string",
"value": "={{ $json.date }}"
},
{
"id": "id-4",
"name": "description",
"type": "string",
"value": "={{ $json.description }}"
},
{
"id": "id-5",
"name": "sourceType",
"type": "string",
"value": "csv_upload"
},
{
"id": "id-6",
"name": "normalizedAt",
"type": "string",
"value": "={{ $now.toISO() }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "a8f3c054-a206-4a16-99d0-2957eb87caa6",
"name": "Merge All Normalized Data",
"type": "n8n-nodes-base.merge",
"position": [
448,
208
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineAll"
},
"typeVersion": 3.2
},
{
"id": "b54e7970-4c2b-478c-9568-57a10757895d",
"name": "Deterministic Matching Logic",
"type": "n8n-nodes-base.code",
"position": [
832,
304
],
"parameters": {
"jsCode": "// Deterministic Matching Logic\n// Groups records by exact matches on recordId, amount, and date fields\n// Calculates match confidence based on number of matching fields\n\nconst items = $input.all();\nconst matchedGroups = {};\nconst results = [];\n\n// Helper function to normalize values for comparison\nfunction normalizeValue(value) {\n if (value === null || value === undefined) return '';\n return String(value).trim().toLowerCase();\n}\n\n// Helper function to normalize date for comparison\nfunction normalizeDate(date) {\n if (!date) return '';\n try {\n const d = new Date(date);\n return d.toISOString().split('T')[0]; // YYYY-MM-DD format\n } catch (e) {\n return String(date).trim();\n }\n}\n\n// Helper function to normalize amount for comparison\nfunction normalizeAmount(amount) {\n if (amount === null || amount === undefined) return '';\n const num = parseFloat(String(amount).replace(/[^0-9.-]/g, ''));\n return isNaN(num) ? '' : num.toFixed(2);\n}\n\n// Process each item and create matching keys\nfor (const item of items) {\n const json = item.json;\n \n const recordId = normalizeValue(json.recordId || json.id || json.transactionId);\n const amount = normalizeAmount(json.amount || json.total || json.value);\n const date = normalizeDate(json.date || json.transactionDate || json.timestamp);\n \n // Create multiple matching keys with different combinations\n const matchingKeys = [];\n \n // Exact match on all three fields (highest confidence)\n if (recordId && amount && date) {\n matchingKeys.push({ key: `${recordId}|${amount}|${date}`, matchedFields: ['recordId', 'amount', 'date'], confidence: 1.0 });\n }\n \n // Match on recordId and amount (high confidence)\n if (recordId && amount) {\n matchingKeys.push({ key: `${recordId}|${amount}`, matchedFields: ['recordId', 'amount'], confidence: 0.85 });\n }\n \n // Match on recordId and date (high confidence)\n if (recordId && date) {\n matchingKeys.push({ key: `${recordId}|${date}`, matchedFields: ['recordId', 'date'], confidence: 0.85 });\n }\n \n // Match on amount and date (medium confidence)\n if (amount && date) {\n matchingKeys.push({ key: `${amount}|${date}`, matchedFields: ['amount', 'date'], confidence: 0.7 });\n }\n \n // Match on recordId only (lower confidence)\n if (recordId) {\n matchingKeys.push({ key: `${recordId}`, matchedFields: ['recordId'], confidence: 0.6 });\n }\n \n // Store item with its matching keys\n for (const matchKey of matchingKeys) {\n if (!matchedGroups[matchKey.key]) {\n matchedGroups[matchKey.key] = {\n items: [],\n matchedFields: matchKey.matchedFields,\n baseConfidence: matchKey.confidence\n };\n }\n matchedGroups[matchKey.key].items.push(json);\n }\n}\n\n// Process matched groups and create output\nfor (const [key, group] of Object.entries(matchedGroups)) {\n if (group.items.length > 1) {\n // Multiple items matched - potential reconciliation\n const matchCount = group.items.length;\n const confidence = group.baseConfidence * Math.min(1.0, matchCount / 2); // Adjust confidence based on match count\n \n results.push({\n matchKey: key,\n matchedFields: group.matchedFields,\n matchCount: matchCount,\n confidence: parseFloat(confidence.toFixed(2)),\n matchType: 'deterministic',\n records: group.items,\n status: confidence >= 0.8 ? 'high_confidence' : 'medium_confidence'\n });\n } else if (group.items.length === 1) {\n // Single item - no match found\n results.push({\n matchKey: key,\n matchedFields: group.matchedFields,\n matchCount: 1,\n confidence: 0,\n matchType: 'no_match',\n records: group.items,\n status: 'unmatched'\n });\n }\n}\n\n// Return results\nreturn results.map(result => ({ json: result }));"
},
"typeVersion": 2
},
{
"id": "895fed31-1878-4834-bdff-834c29948de5",
"name": "Check Match Quality",
"type": "n8n-nodes-base.if",
"position": [
1008,
304
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": false,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "id-1",
"operator": {
"type": "number",
"operation": "lt"
},
"leftValue": "={{ $('Deterministic Matching Logic').item.json.matchConfidence }}",
"rightValue": "={{ $('Workflow Configuration').first().json.fuzzyMatchThreshold }}"
}
]
}
},
"typeVersion": 2.3
},
{
"id": "73cfb80a-0342-4542-a099-9ca83d8b045e",
"name": "AI Fuzzy Matching Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1248,
528
],
"parameters": {
"text": "=Records to match: {{ $json.unmatchedRecords }}",
"options": {
"systemMessage": "You are a financial data reconciliation specialist. Your task is to analyze unmatched financial records and identify potential matches using fuzzy matching techniques.\n\nFor each unmatched record, you should:\n1. Compare transaction descriptions using semantic similarity\n2. Check for near-matches in amounts (within 1% tolerance)\n3. Look for date matches within a 3-day window\n4. Consider vendor name variations and abbreviations\n5. Return matched pairs with confidence scores\n\nReturn your analysis in the structured format defined by the output parser."
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 3
},
{
"id": "7abbe9b8-2a0b-48d9-81c0-39b0a80df771",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1248,
864
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-mini"
},
"options": {},
"builtInTools": {}
},
"typeVersion": 1.3
},
{
"id": "2a37407e-1fd9-46d5-a942-de40e246f47d",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1408,
848
],
"parameters": {
"jsonSchemaExample": "{\n\t\"matchedPairs\": [\n\t\t{\n\t\t\t\"sourceRecord\": {},\n\t\t\t\"targetRecord\": {},\n\t\t\t\"confidenceScore\": 0.95,\n\t\t\t\"matchReason\": \"Exact match on transaction ID and amount\"\n\t\t}\n\t],\n\t\"unmatchedRecords\": []\n}"
},
"typeVersion": 1.3
},
{
"id": "295397ed-0102-4df9-a2cf-446a85439e49",
"name": "Merge Matched Results",
"type": "n8n-nodes-base.merge",
"position": [
1680,
304
],
"parameters": {
"mode": "combineAll"
},
"typeVersion": 3.2
},
{
"id": "54f8e770-f6f8-4b49-bb2c-78962732ed6f",
"name": "Calculate Confidence Scores",
"type": "n8n-nodes-base.code",
"position": [
1872,
304
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "// Calculate final confidence scores by combining deterministic and AI fuzzy match scores\n// Normalize to 0-1 range and add audit trail metadata\n\nconst item = $input.item.json;\n\n// Extract scores from different matching stages\nconst deterministicScore = item.deterministicMatchScore || 0;\nconst aiScore = item.aiMatchScore || 0;\nconst hasAiMatch = item.aiMatchScore !== undefined;\n\n// Weight configuration\nconst DETERMINISTIC_WEIGHT = 0.6;\nconst AI_WEIGHT = 0.4;\n\n// Calculate combined confidence score\nlet finalConfidence;\nif (hasAiMatch) {\n // Combine both scores with weights\n finalConfidence = (deterministicScore * DETERMINISTIC_WEIGHT) + (aiScore * AI_WEIGHT);\n} else {\n // Only deterministic match available\n finalConfidence = deterministicScore;\n}\n\n// Normalize to 0-1 range\nfinalConfidence = Math.max(0, Math.min(1, finalConfidence));\n\n// Determine confidence level\nlet confidenceLevel;\nif (finalConfidence >= 0.9) {\n confidenceLevel = 'HIGH';\n} else if (finalConfidence >= 0.7) {\n confidenceLevel = 'MEDIUM';\n} else if (finalConfidence >= 0.5) {\n confidenceLevel = 'LOW';\n} else {\n confidenceLevel = 'VERY_LOW';\n}\n\n// Build audit trail\nconst auditTrail = {\n timestamp: new Date().toISOString(),\n deterministicScore: deterministicScore,\n aiScore: hasAiMatch ? aiScore : null,\n finalConfidence: finalConfidence,\n confidenceLevel: confidenceLevel,\n matchingMethod: hasAiMatch ? 'HYBRID' : 'DETERMINISTIC',\n weights: {\n deterministic: DETERMINISTIC_WEIGHT,\n ai: AI_WEIGHT\n }\n};\n\n// Return enriched item with confidence scores and audit trail\nreturn {\n json: {\n ...item,\n finalConfidence: finalConfidence,\n confidenceLevel: confidenceLevel,\n confidencePercentage: Math.round(finalConfidence * 100),\n auditTrail: auditTrail\n }\n};"
},
"typeVersion": 2
},
{
"id": "e96842c2-5bc0-44e0-b3e9-bfcbb62a80e6",
"name": "Route by Confidence Threshold",
"type": "n8n-nodes-base.if",
"position": [
2080,
320
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": false,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "id-1",
"operator": {
"type": "number",
"operation": "gte"
},
"leftValue": "={{ $json.finalConfidence }}",
"rightValue": "={{ $('Workflow Configuration').first().json.confidenceThreshold }}"
}
]
}
},
"typeVersion": 2.3
},
{
"id": "b10d37cf-b377-4397-8b67-f358bfc5da07",
"name": "Flag for Human Review",
"type": "n8n-nodes-base.set",
"position": [
2320,
400
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "reviewStatus",
"type": "string",
"value": "pending_human_review"
},
{
"id": "id-2",
"name": "reviewReason",
"type": "string",
"value": "Low confidence match - requires manual verification"
},
{
"id": "id-3",
"name": "flaggedAt",
"type": "string",
"value": "={{ $now.toISO() }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "52559270-484a-49d0-847e-f004518abb02",
"name": "Mark as Auto-Reconciled",
"type": "n8n-nodes-base.set",
"position": [
2320,
256
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "reviewStatus",
"type": "string",
"value": "auto_reconciled"
},
{
"id": "id-2",
"name": "reconciledAt",
"type": "string",
"value": "={{ $now.toISO() }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "fe27e284-4bc7-446b-85fc-1cd03f8b8f81",
"name": "Merge All Results",
"type": "n8n-nodes-base.merge",
"position": [
2640,
352
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "4cdd473a-2795-43ed-a464-a874d458e3ff",
"name": "Log to Reconciliation Report",
"type": "n8n-nodes-base.googleSheets",
"position": [
2864,
352
],
"parameters": {
"columns": {
"value": null,
"mappingMode": "autoMapInputData"
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Reconciliation Report"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Google Sheets Document ID__>"
}
},
"typeVersion": 4.7
},
{
"id": "2682e628-ed05-4fd2-8feb-43d9caff7470",
"name": "Notify Finance Team",
"type": "n8n-nodes-base.slack",
"position": [
3120,
352
],
"parameters": {
"text": "=Reconciliation Complete!\n\nTotal Records Processed: {{ $json.totalRecords }}\nAuto-Reconciled: {{ $json.autoReconciledCount }}\nPending Review: {{ $json.pendingReviewCount }}\n\nView full report: {{ $json.reportUrl }}",
"select": "channel",
"channelId": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__Slack Channel ID or Name__>"
},
"otherOptions": {}
},
"typeVersion": 2.4
},
{
"id": "3d42b58b-ab5e-4969-bbd9-96444b55ee6c",
"name": "Merge All Normalized Data1",
"type": "n8n-nodes-base.merge",
"position": [
448,
432
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineAll"
},
"typeVersion": 3.2
},
{
"id": "e879468a-0a17-4a40-ada7-79e8023272e2",
"name": "Merge All Normalized Data2",
"type": "n8n-nodes-base.merge",
"position": [
640,
304
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineAll"
},
"typeVersion": 3.2
},
{
"id": "c8f83a37-b017-4749-99da-e51966fabb13",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1664,
64
],
"parameters": {
"width": 560,
"height": 528,
"content": "\n## How it works\nThis workflow automates reconciliation across bank statements, invoices, ERP systems, and CSV uploads. It standardizes all data into a unified format and performs deterministic matching using fields like ID, amount, and date.\n\nFor unmatched records, AI fuzzy matching identifies potential matches using descriptions, amount tolerance, and date proximity. A final confidence score is calculated, auto-reconciling high-confidence matches while flagging others for review.\n\n## Setup\n\n- Configure webhook to receive financial data \n- Set matching keys and confidence thresholds \n- Connect OpenAI for fuzzy matching \n- Connect Google Sheets for reporting \n- Connect Slack for notifications \n- Ensure input data follows expected formats \n- Test with sample data before activating \n"
},
"typeVersion": 1
},
{
"id": "d97902db-baa8-41af-8e92-60ed7b090c42",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-864,
144
],
"parameters": {
"color": 7,
"width": 400,
"height": 352,
"content": "## Data Input\nReceives financial data via webhook from multiple sources and Defines matching keys, thresholds, and reconciliation rules."
},
"typeVersion": 1
},
{
"id": "1f5d7acb-20d4-4968-ae11-15a950fb1d82",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-432,
144
],
"parameters": {
"color": 7,
"width": 256,
"height": 352,
"content": "## Source Routing\nDetects data type and routes to correct normalization flow.)"
},
"typeVersion": 1
},
{
"id": "d5f1e7f2-2466-407a-bf7e-863fefa466f5",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-96,
-80
],
"parameters": {
"color": 7,
"width": 272,
"height": 848,
"content": "## Data Normalization\nConverts bank, invoice, ERP, and CSV data into a unified schema."
},
"typeVersion": 1
},
{
"id": "57d64771-fda3-4bd2-9b0a-d5e60537f5ae",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
384,
80
],
"parameters": {
"color": 7,
"width": 384,
"height": 528,
"content": "## Data Merge\nCombines all normalized records for comparison."
},
"typeVersion": 1
},
{
"id": "f93866d8-35f9-4065-8a18-d16ce408a60a",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
800,
128
],
"parameters": {
"color": 7,
"width": 352,
"height": 384,
"content": "## Deterministic Matching\nMatches records using exact fields like ID, amount, and date."
},
"typeVersion": 1
},
{
"id": "1d8eb26d-23ee-4ca0-9620-3bd8775e7559",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1200,
416
],
"parameters": {
"color": 7,
"width": 336,
"height": 352,
"content": "## AI Fuzzy Matching\nUses AI to find near matches based on text, amount, and date."
},
"typeVersion": 1
},
{
"id": "10ca8421-c5f2-4033-a2e5-bf8f845322e1",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
1584,
192
],
"parameters": {
"color": 7,
"width": 432,
"height": 272,
"content": "## Confidence Scoring\nCombines matching results into final confidence score with audit trail."
},
"typeVersion": 1
},
{
"id": "89ed1034-6845-4de2-8a5c-5a235c58bf7e",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
2048,
176
],
"parameters": {
"color": 7,
"width": 464,
"height": 416,
"content": "## Decision Routing\nRoutes high-confidence matches or flags low-confidence for review."
},
"typeVersion": 1
},
{
"id": "ef0d6bea-dbd9-42cb-b9e6-6fdac191bbd4",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
2832,
176
],
"parameters": {
"color": 7,
"width": 480,
"height": 416,
"content": "## Reporting\nLogs reconciliation results into Google Sheets and Sends summary of reconciliation results via Slack."
},
"typeVersion": 1
}
],
"connections": {
"Extract CSV Data": {
"main": [
[
{
"node": "Normalize CSV Schema",
"type": "main",
"index": 0
}
]
]
},
"Merge All Results": {
"main": [
[
{
"node": "Log to Reconciliation Report",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Fuzzy Matching Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Check Match Quality": {
"main": [
[
{
"node": "Merge Matched Results",
"type": "main",
"index": 0
}
],
[
{
"node": "AI Fuzzy Matching Agent",
"type": "main",
"index": 0
}
]
]
},
"Normalize CSV Schema": {
"main": [
[
{
"node": "Merge All Normalized Data",
"type": "main",
"index": 0
}
]
]
},
"Normalize ERP Schema": {
"main": [
[
{
"node": "Merge All Normalized Data1",
"type": "main",
"index": 1
}
]
]
},
"Flag for Human Review": {
"main": [
[
{
"node": "Merge All Results",
"type": "main",
"index": 0
}
]
]
},
"Merge Matched Results": {
"main": [
[
{
"node": "Calculate Confidence Scores",
"type": "main",
"index": 0
}
]
]
},
"Check Data Source Type": {
"main": [
[
{
"node": "Normalize Bank Statement Schema",
"type": "main",
"index": 0
}
],
[
{
"node": "Normalize Invoice Schema",
"type": "main",
"index": 0
},
{
"node": "Normalize ERP Schema",
"type": "main",
"index": 0
},
{
"node": "Extract CSV Data",
"type": "main",
"index": 0
}
]
]
},
"Workflow Configuration": {
"main": [
[
{
"node": "Check Data Source Type",
"type": "main",
"index": 0
}
]
]
},
"AI Fuzzy Matching Agent": {
"main": [
[
{
"node": "Merge Matched Results",
"type": "main",
"index": 1
}
]
]
},
"Mark as Auto-Reconciled": {
"main": [
[
{
"node": "Merge All Results",
"type": "main",
"index": 1
}
]
]
},
"Normalize Invoice Schema": {
"main": [
[
{
"node": "Merge All Normalized Data1",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "AI Fuzzy Matching Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Merge All Normalized Data": {
"main": [
[
{
"node": "Merge All Normalized Data2",
"type": "main",
"index": 0
}
]
]
},
"Merge All Normalized Data1": {
"main": [
[
{
"node": "Merge All Normalized Data2",
"type": "main",
"index": 1
}
]
]
},
"Merge All Normalized Data2": {
"main": [
[
{
"node": "Deterministic Matching Logic",
"type": "main",
"index": 0
}
]
]
},
"Calculate Confidence Scores": {
"main": [
[
{
"node": "Route by Confidence Threshold",
"type": "main",
"index": 0
}
]
]
},
"Deterministic Matching Logic": {
"main": [
[
{
"node": "Check Match Quality",
"type": "main",
"index": 0
}
]
]
},
"Log to Reconciliation Report": {
"main": [
[
{
"node": "Notify Finance Team",
"type": "main",
"index": 0
}
]
]
},
"Route by Confidence Threshold": {
"main": [
[
{
"node": "Mark as Auto-Reconciled",
"type": "main",
"index": 0
}
],
[
{
"node": "Flag for Human Review",
"type": "main",
"index": 0
}
]
]
},
"Normalize Bank Statement Schema": {
"main": [
[
{
"node": "Merge All Normalized Data",
"type": "main",
"index": 1
}
]
]
},
"Webhook - Receive Financial Data": {
"main": [
[
{
"node": "Workflow Configuration",
"type": "main",
"index": 0
}
]
]
}
}
}
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About this workflow
This workflow automates financial reconciliation across multiple data sources such as bank statements, invoices, ERP systems, and CSV uploads.
Source: https://n8n.io/workflows/14276/ — original creator credit. Request a take-down →
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