{ "id": "mHSoMMyypmRzfVZn", "name": "CFO forecasting Agent", "tags": [], "nodes": [ { "id": "b946638e-ba68-4d73-816e-00f3a63d138f", "name": "Structured Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ 1420, 220 ], "parameters": { "jsonSchemaExample": "{\n \"forecast\": {\n \"June 2025\": \"$X,XXX.XX\",\n \"July 2025\": \"$X,XXX.XX\",\n \"August 2025\": \"$X,XXX.XX\"\n },\n \"trend\": \"Increasing / Decreasing / Stable\",\n \"confidence\": \"High / Medium / Low\",\n \"insights\": \"Short explanation of why this trend is predicted.\"\n}" }, "typeVersion": 1.2 }, { "id": "d80c3670-e8c8-43ee-ba12-2e0e18b99862", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 1180, 220 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "name": "" } }, "typeVersion": 1.2 }, { "id": "bb75cafb-9dad-4952-89af-0658c4d88aa4", "name": "Pinecone Vector Store", "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone", "position": [ 1200, 400 ], "parameters": { "mode": "retrieve-as-tool", "options": {}, "toolName": "Sales_data", "pineconeIndex": { "__rl": true, "mode": "list", "value": "new", "cachedResultName": "new" }, "toolDescription": "The data about stripe sales" }, "credentials": { "pineconeApi": { "name": "" } }, "typeVersion": 1.1 }, { "id": "7d370700-89d9-4163-8070-4a0c643531ca", "name": "Embeddings OpenAI", "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi", "position": [ 1140, 600 ], "parameters": { "options": {} }, "credentials": { "openAiApi": { "name": "" } }, "typeVersion": 1.2 }, { "id": "81de1ecf-75de-44fd-9e62-c381e907c1e1", "name": "Run Daily Forecast", "type": "n8n-nodes-base.scheduleTrigger", "position": [ 0, 0 ], "parameters": { "rule": { "interval": [ { "triggerAtHour": 9 } ] } }, "typeVersion": 1.2 }, { "id": "9ce2e0e4-8784-4ed9-9499-b5f54241d04e", "name": "Fetch Stripe Charges", "type": "n8n-nodes-base.stripe", "position": [ 220, 0 ], "parameters": { "resource": "charge", "operation": "getAll", "returnAll": true }, "typeVersion": 1 }, { "id": "c115eb0c-6877-46db-bf03-55e48527dbc5", "name": "Summarize Sales", "type": "n8n-nodes-base.code", "position": [ 440, 0 ], "parameters": { "jsCode": "const charges = items.map(item => item.json);\nconst summary = charges.reduce((acc, charge) => {\n const date = new Date(charge.created * 1000).toISOString().split(\"T\")[0];\n acc[date] = (acc[date] || 0) + charge.amount / 100;\n return acc;\n}, {});\nreturn [{ json: { summary } }];\n" }, "typeVersion": 2 }, { "id": "fb33581a-9f41-49d7-a722-a68dfe5bc265", "name": "Prepare data", "type": "n8n-nodes-base.set", "position": [ 660, 0 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "6aa7f5d2-3aa4-4d4c-85df-0d56bb7b6c9e", "name": "summary", "type": "string", "value": "={{ $json.summary }}" } ] } }, "typeVersion": 3.4 }, { "id": "d3458681-2654-4e22-8b2d-1711b60ed592", "name": "Forecaster agent", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 1240, 0 ], "parameters": { "text": "=You are a CFO AI Agent. Based on the following Stripe sales data:\n\n{{ $json.summary }}\n\nAnalyze the trends, identify any patterns (growth, decline, seasonality), and forecast expected daily or weekly revenue for the next 3 months.", "options": {}, "promptType": "define", "hasOutputParser": true }, "typeVersion": 1.9 }, { "id": "325e4952-868c-460a-aa78-2e718477cc78", "name": "Save Forecast to Supabase", "type": "n8n-nodes-base.supabase", "position": [ 2100, -160 ], "parameters": { "dataToSend": "autoMapInputData" }, "typeVersion": 1 }, { "id": "9fd6efab-edc6-49be-9516-f2d36e1995b2", "name": "Log Forecast in Google Sheets", "type": "n8n-nodes-base.googleSheets", "position": [ 2100, 120 ], "parameters": { "columns": { "value": { "trend": "={{ $json.output.trend }}", "forecast": "={{ $json.output.forecast }}", "insights": "={{ $json.output.insights }}", "confidence": "={{ $json.output.confidence }}" }, "schema": [ { "id": "forecast", "type": "string", "display": true, "required": false, "displayName": "forecast", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "trend", "type": "string", "display": true, "required": false, "displayName": "trend", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "confidence", "type": "string", "display": true, "required": false, "displayName": "confidence", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "insights", "type": "string", "display": true, "required": false, "displayName": "insights", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "gid=0", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/108tyyL--yUCbDk4drB__eztLSwjlxcmoRkqYsFnMLrY/edit#gid=0", "cachedResultName": "Sheet1" }, "documentId": { "__rl": true, "mode": "list", "value": "108tyyL--yUCbDk4drB__eztLSwjlxcmoRkqYsFnMLrY", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/108tyyL--yUCbDk4drB__eztLSwjlxcmoRkqYsFnMLrY/edit?usp=drivesdk", "cachedResultName": "CFO Forecasting" } }, "credentials": { "googleSheetsOAuth2Api": { "name": "" } }, "typeVersion": 4.5 }, { "id": "241e625d-7019-4919-9f93-137461ad94bf", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ -40, -1820 ], "parameters": { "color": 3, "width": 840, "height": 2120, "content": "## 1\ufe0f\u20e3 **\ud83d\udd01 Data Retrieval & Preprocessing**\n\n**Nodes:**\n\n* \ud83d\udd52 `Run Daily Forecast`\n* \ud83d\udfe6 `Fetch Stripe Charges`\n* \ud83e\udde9 `Summarize Daily Sales`\n* \u270f\ufe0f `Prepare Forecast Prompt`\n\n---\n\n### \ud83d\udd52 `Run Daily Forecast`\n\n**Type:** Cron Trigger\n**Purpose:**\nAutomatically runs the workflow every day to keep forecasts updated with the latest sales data.\n\n\ud83d\udd27 **Configuration:**\n\n* Schedule: Daily at 6 AM UTC (or as needed)\n\n---\n\n### \ud83d\udfe6 `Fetch Stripe Charges`\n\n**Type:** Stripe Node\n**Purpose:**\nRetrieves all successful transactions from Stripe in a defined timeframe.\n\n\ud83d\udce5 **Details:**\n\n* Resource: `Charges`\n* Operation: `Get Many`\n* Filters:\n\n * `created[gte]` (e.g. last 30 days)\n * `status: succeeded`\n* Expansion (optional): `data.customer` for customer context\n\n\u2705 **Output:** Raw Stripe sales data with timestamps and amounts\n\n---\n\n### \ud83e\udde9 `Summarize Daily Sales`\n\n**Type:** Code Node\n**Purpose:**\nProcesses Stripe charges and summarizes revenue per day.\n\n\ud83e\udde0 **Logic:**\n\n* Converts Unix timestamps to `YYYY-MM-DD`\n* Aggregates total revenue per day\n* Converts cents to dollars\n\n\ud83d\udce6 **Output Sample:**\n\n```json\n{\n \"2025-05-01\": 1245.50,\n \"2025-05-02\": 980.00\n}\n```\n\n---\n\n### \u270f\ufe0f `Prepare Forecast Prompt`\n\n**Type:** Edit Fields / Function\n**Purpose:**\nFormats the summary into a natural language prompt for OpenAI.\n\n\ud83e\udde0 **Example Prompt:**\n\n```txt\nGiven the following sales data:\n{ \"2025-05-01\": 1245.50, ... }\n\nPredict trends and forecast sales for the next 3 months.\n```\n\n\ud83e\uddfe **Output:** `prompt` (String) \u2192 sent to the AI Agent\n" }, "typeVersion": 1 }, { "id": "f60c6c15-8449-457a-aaad-2ebca8d75318", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 940, -1880 ], "parameters": { "color": 6, "width": 840, "height": 2680, "content": "## 2\ufe0f\u20e3 **\ud83e\udd16 AI Agent Forecasting**\n\n**Nodes:**\n\n* \ud83e\udd16 `Forecast with OpenAI Agent`\n* \ud83e\udde0 `OpenAI GPT-4 Model`\n* \ud83d\udcc4 `Extract Forecast Output`\n* \ud83c\udf32 `Store Context in Pinecone` *(Optional)*\n* \ud83e\uddec `Generate Embeddings` *(Optional)*\n\n---\n\n### \ud83e\udd16 `Forecast with OpenAI Agent`\n\n**Type:** Tools Agent\n**Purpose:**\nActs as an intelligent agent that reads the sales summary and responds with forecasts and reasoning.\n\n\ud83e\udde0 **Prompt Input:**\nPassed from `Prepare Forecast Prompt`\n\n\ud83d\udcac **Uses:**\n\n* Model: `GPT-4`\n* Output Parser: Structured JSON format\n\n\ud83d\udcc8 **Forecast Intent:**\nPredicts next 3 months, identifies trends, and gives a confidence level\n\n---\n\n### \ud83e\udde0 `OpenAI GPT-4 Model`\n\n**Type:** OpenAI Node\n**Purpose:**\nHandles the natural language generation based on the supplied prompt.\n\n\ud83e\uddfe **Configuration:**\n\n* Model: `gpt-4` or `gpt-4-turbo`\n* Temperature: `0.2` (more deterministic)\n* Max Tokens: `1000`\n\n---\n\n### \ud83d\udcc4 `Extract Forecast Output`\n\n**Type:** Structured Output Parser\n**Purpose:**\nParses the GPT response into usable JSON format.\n\n\ud83d\udce6 **Expected Output:**\n\n```json\n{\n \"forecast\": {\n \"June\": \"$15,000.00\",\n \"July\": \"$16,500.00\",\n \"August\": \"$17,200.00\"\n },\n \"trend\": \"Increasing\",\n \"confidence\": \"High\",\n \"insights\": \"Sales show strong momentum...\"\n}\n```\n\n---\n\n### \ud83c\udf32 `Store Context in Pinecone` *(optional)*\n\n**Type:** Vector Store\n**Purpose:**\nIndexes past data for retrieval-based prompting (RAG). Useful for long-term memory.\n\n---\n\n### \ud83e\uddec `Generate Embeddings` *(optional)*\n\n**Type:** Embeddings Node\n**Purpose:**\nConverts text into vector format before inserting into Pinecone." }, "typeVersion": 1 }, { "id": "8e9b2ea7-58bb-4f62-a69c-eed70032019c", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 1920, -1220 ], "parameters": { "color": 5, "width": 460, "height": 1560, "content": "## 3\ufe0f\u20e3 **\ud83d\udce6 Storage & Reporting**\n\n**Nodes:**\n\n* \ud83d\udfe9 `Save Forecast to Supabase`\n* \ud83d\udcca `Log Forecast in Google Sheets`\n\n---\n\n### \ud83d\udfe9 `Save Forecast to Supabase`\n\n**Type:** Supabase Node\n**Purpose:**\nStores all forecast results for analytics, versioning, or historical comparisons.\n\n\ud83d\udee2\ufe0f **Table:** `forecasts`\n\ud83e\uddfe **Columns Example:**\n\n| timestamp | raw\\_data | forecast\\_data |\n| ---------- | --------- | -------------- |\n| 2025-05-29 | {...} | {...} |\n\n---\n\n### \ud83d\udcca `Log Forecast in Google Sheets`\n\n**Type:** Google Sheets Node\n**Purpose:**\nPushes structured data into a visual format for reporting dashboards or human review.\n\n\ud83d\udccb **Column Format:**\n\n| Date | Forecast (USD) | Trend | Confidence | Insights |\n| ---------- | -------------- | ---------- | ---------- | -------------------------- |\n| 2025-05-29 | \\$15,000.00 | Increasing | High | Sales rising at 10% weekly |\n\n---\n\n## \u2705 Summary Flow\n\n```txt\n\ud83d\udd01 Sales Data (Stripe) \n \u2192 \ud83e\udde0 Forecast Agent (OpenAI) \n \u2192 \ud83d\udce6 Stored in Supabase \n \u2192 \ud83d\udcca Reported in Google Sheets" }, "typeVersion": 1 }, { "id": "7d1186c9-cba1-4876-a405-fa67773b8dad", "name": "Sticky Note9", "type": "n8n-nodes-base.stickyNote", "position": [ -1840, -1800 ], "parameters": { "color": 4, "width": 1300, "height": 320, "content": "=======================================\n WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n - YouTube: https://www.youtube.com/@YaronBeen/videos\n - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n" }, "typeVersion": 1 }, { "id": "2b9e9108-8084-4e3f-a620-5bee07040bc3", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ -1840, -1460 ], "parameters": { "color": 4, "width": 1289, "height": 4778, "content": "# \ud83d\udcca CFO Forecasting Agent \u2013 Workflow Documentation\n\n---\n\n## 1\ufe0f\u20e3 **\ud83d\udd01 Data Retrieval & Preprocessing**\n\n**Nodes:**\n\n* \ud83d\udd52 `Run Daily Forecast`\n* \ud83d\udfe6 `Fetch Stripe Charges`\n* \ud83e\udde9 `Summarize Daily Sales`\n* \u270f\ufe0f `Prepare Forecast Prompt`\n\n---\n\n### \ud83d\udd52 `Run Daily Forecast`\n\n**Type:** Cron Trigger\n**Purpose:**\nAutomatically runs the workflow every day to keep forecasts updated with the latest sales data.\n\n\ud83d\udd27 **Configuration:**\n\n* Schedule: Daily at 6 AM UTC (or as needed)\n\n---\n\n### \ud83d\udfe6 `Fetch Stripe Charges`\n\n**Type:** Stripe Node\n**Purpose:**\nRetrieves all successful transactions from Stripe in a defined timeframe.\n\n\ud83d\udce5 **Details:**\n\n* Resource: `Charges`\n* Operation: `Get Many`\n* Filters:\n\n * `created[gte]` (e.g. last 30 days)\n * `status: succeeded`\n* Expansion (optional): `data.customer` for customer context\n\n\u2705 **Output:** Raw Stripe sales data with timestamps and amounts\n\n---\n\n### \ud83e\udde9 `Summarize Daily Sales`\n\n**Type:** Code Node\n**Purpose:**\nProcesses Stripe charges and summarizes revenue per day.\n\n\ud83e\udde0 **Logic:**\n\n* Converts Unix timestamps to `YYYY-MM-DD`\n* Aggregates total revenue per day\n* Converts cents to dollars\n\n\ud83d\udce6 **Output Sample:**\n\n```json\n{\n \"2025-05-01\": 1245.50,\n \"2025-05-02\": 980.00\n}\n```\n\n---\n\n### \u270f\ufe0f `Prepare Forecast Prompt`\n\n**Type:** Edit Fields / Function\n**Purpose:**\nFormats the summary into a natural language prompt for OpenAI.\n\n\ud83e\udde0 **Example Prompt:**\n\n```txt\nGiven the following sales data:\n{ \"2025-05-01\": 1245.50, ... }\n\nPredict trends and forecast sales for the next 3 months.\n```\n\n\ud83e\uddfe **Output:** `prompt` (String) \u2192 sent to the AI Agent\n\n---\n\n## 2\ufe0f\u20e3 **\ud83e\udd16 AI Agent Forecasting**\n\n**Nodes:**\n\n* \ud83e\udd16 `Forecast with OpenAI Agent`\n* \ud83e\udde0 `OpenAI GPT-4 Model`\n* \ud83d\udcc4 `Extract Forecast Output`\n* \ud83c\udf32 `Store Context in Pinecone` *(Optional)*\n* \ud83e\uddec `Generate Embeddings` *(Optional)*\n\n---\n\n### \ud83e\udd16 `Forecast with OpenAI Agent`\n\n**Type:** Tools Agent\n**Purpose:**\nActs as an intelligent agent that reads the sales summary and responds with forecasts and reasoning.\n\n\ud83e\udde0 **Prompt Input:**\nPassed from `Prepare Forecast Prompt`\n\n\ud83d\udcac **Uses:**\n\n* Model: `GPT-4`\n* Output Parser: Structured JSON format\n\n\ud83d\udcc8 **Forecast Intent:**\nPredicts next 3 months, identifies trends, and gives a confidence level\n\n---\n\n### \ud83e\udde0 `OpenAI GPT-4 Model`\n\n**Type:** OpenAI Node\n**Purpose:**\nHandles the natural language generation based on the supplied prompt.\n\n\ud83e\uddfe **Configuration:**\n\n* Model: `gpt-4` or `gpt-4-turbo`\n* Temperature: `0.2` (more deterministic)\n* Max Tokens: `1000`\n\n---\n\n### \ud83d\udcc4 `Extract Forecast Output`\n\n**Type:** Structured Output Parser\n**Purpose:**\nParses the GPT response into usable JSON format.\n\n\ud83d\udce6 **Expected Output:**\n\n```json\n{\n \"forecast\": {\n \"June\": \"$15,000.00\",\n \"July\": \"$16,500.00\",\n \"August\": \"$17,200.00\"\n },\n \"trend\": \"Increasing\",\n \"confidence\": \"High\",\n \"insights\": \"Sales show strong momentum...\"\n}\n```\n\n---\n\n### \ud83c\udf32 `Store Context in Pinecone` *(optional)*\n\n**Type:** Vector Store\n**Purpose:**\nIndexes past data for retrieval-based prompting (RAG). Useful for long-term memory.\n\n---\n\n### \ud83e\uddec `Generate Embeddings` *(optional)*\n\n**Type:** Embeddings Node\n**Purpose:**\nConverts text into vector format before inserting into Pinecone.\n\n---\n\n## 3\ufe0f\u20e3 **\ud83d\udce6 Storage & Reporting**\n\n**Nodes:**\n\n* \ud83d\udfe9 `Save Forecast to Supabase`\n* \ud83d\udcca `Log Forecast in Google Sheets`\n\n---\n\n### \ud83d\udfe9 `Save Forecast to Supabase`\n\n**Type:** Supabase Node\n**Purpose:**\nStores all forecast results for analytics, versioning, or historical comparisons.\n\n\ud83d\udee2\ufe0f **Table:** `forecasts`\n\ud83e\uddfe **Columns Example:**\n\n| timestamp | raw\\_data | forecast\\_data |\n| ---------- | --------- | -------------- |\n| 2025-05-29 | {...} | {...} |\n\n---\n\n### \ud83d\udcca `Log Forecast in Google Sheets`\n\n**Type:** Google Sheets Node\n**Purpose:**\nPushes structured data into a visual format for reporting dashboards or human review.\n\n\ud83d\udccb **Column Format:**\n\n| Date | Forecast (USD) | Trend | Confidence | Insights |\n| ---------- | -------------- | ---------- | ---------- | -------------------------- |\n| 2025-05-29 | \\$15,000.00 | Increasing | High | Sales rising at 10% weekly |\n\n---\n\n## \u2705 Summary Flow\n\n```txt\n\ud83d\udd01 Sales Data (Stripe) \n \u2192 \ud83e\udde0 Forecast Agent (OpenAI) \n \u2192 \ud83d\udce6 Stored in Supabase \n \u2192 \ud83d\udcca Reported in Google Sheets\n```\n" }, "typeVersion": 1 } ], "active": false, "settings": { "executionOrder": "v1" }, "versionId": "56196260-ac1a-4ef1-87c1-d5a8e1eb438f", "connections": { "Prepare data": { "main": [ [ { "node": "Forecaster agent", "type": "main", "index": 0 } ] ] }, "Summarize Sales": { "main": [ [ { "node": "Prepare data", "type": "main", "index": 0 } ] ] }, "Forecaster agent": { "main": [ [ { "node": "Save Forecast to Supabase", "type": "main", "index": 0 }, { "node": "Log Forecast in Google Sheets", "type": "main", "index": 0 } ] ] }, "Embeddings OpenAI": { "ai_embedding": [ [ { "node": "Pinecone Vector Store", "type": "ai_embedding", "index": 0 } ] ] }, "OpenAI Chat Model": { "ai_languageModel": [ [ { "node": "Forecaster agent", "type": "ai_languageModel", "index": 0 } ] ] }, "Run Daily Forecast": { "main": [ [ { "node": "Fetch Stripe Charges", "type": "main", "index": 0 } ] ] }, "Fetch Stripe Charges": { "main": [ [ { "node": "Summarize Sales", "type": "main", "index": 0 } ] ] }, "Pinecone Vector Store": { "ai_tool": [ [ { "node": "Forecaster agent", "type": "ai_tool", "index": 0 } ] ] }, "Structured Output Parser": { "ai_outputParser": [ [ { "node": "Forecaster agent", "type": "ai_outputParser", "index": 0 } ] ] } } }