{"workflow":{"id":14546,"name":"Generate Financial Risk Reports 📈 from ElevenLabs interviews 🎙️using OpenAI","views":9,"recentViews":1,"totalViews":9,"createdAt":"2026-04-01T09:43:38.865Z","description":"This workflow automates the process of receiving a post-call audio file and transcription from [ElevenLabs](https://try.elevenlabs.io/ahkbf00hocnu), processing them, and generating a financial risk report.\n\n---\n\n### Key Advantages\n\n#### 1. ✅ End-to-End Automation\n\nThe workflow fully automates the process from raw input (audio/transcript) to final delivery (email report), eliminating manual intervention.\n\n#### 2. ✅ AI-Powered Decision Making\n\nIt leverages language models to:\n\n* Analyze qualitative interview responses\n* Convert them into quantitative scores\n* Produce consistent and objective evaluations\n\n#### 3. ✅ Structured Data Extraction\n\nAutomatically extracts critical business information, reducing human error and ensuring standardized outputs.\n\n#### 4. ✅ Scalability\n\nThe webhook-based architecture allows the system to handle large volumes of interviews in parallel without additional effort.\n\n#### 5. ✅ Modular & Extensible Design\n\nEach step (audio processing, extraction, scoring, reporting) is modular, making it easy to:\n\n* Replace models\n* Add new analysis layers\n* Integrate additional services\n\n#### 6. ✅ Professional Output Generation\n\nGenerates clean, ready-to-send HTML reports compatible with email clients, improving communication with stakeholders.\n\n#### 7. ✅ Data Traceability & Storage\n\nAudio files are stored in Google Drive, ensuring:\n\n* Auditability\n* Easy retrieval of original data\n\n#### 8. ✅ Consistency & Standardization\n\nThe evaluation logic ensures that all interviews are assessed using the same criteria, reducing subjective bias.\n\n---\n\n### How it works\n\n1.  **Receiving and Routing Data**: The workflow starts with a **Webhook** that listens for incoming data from ElevenLabs. A **Switch** node then routes the data based on the `body.type` field.\n    - **Post Call Audio**: If the type is `post_call_audio`, the workflow processes the audio.\n    - **Post Call Transcription**: If the type is `post_call_transcription`, the workflow processes the transcription.\n\n2.  **Audio Processing Path**: For an audio file, a **Code** node extracts the Base64 audio data and the `conversation_id` from the webhook payload. It converts the Base64 string into a binary audio buffer (MP3). This binary data is then passed to a **Google Drive** node, which uploads the file to a specified folder (the user's root folder).\n\n3.  **Transcription Processing Path**: For a transcription, a **Set** node extracts the transcript array from the payload. A subsequent **Code** node processes this array, combining all messages from the conversation into a single, readable full text string, prefixed by the speaker's role.\n\n4.  **Data Enrichment and Analysis**: The full transcript text is then used by two nodes in parallel:\n    - **Information Extractor**: This LangChain node uses an OpenAI model (`gpt-5-mini`) to extract structured data from the text, specifically the `company_name`, the CEO's `name`, the `address`, and the `vat_number`.\n    - **Calculate Rating**: This LangChain node uses another OpenAI model to perform a quantitative evaluation. It follows a provided system prompt to assign a numerical `score`, a final `verdict` (POSITIVE/NEUTRAL/NEGATIVE), and a `reason` based on the interviewee's responses. Its output is parsed by a **Structured Output Parser** to ensure it is valid JSON.\n\n5.  **Report Generation and Delivery**: The outputs from the **Information Extractor** and **Calculate Rating** nodes are merged into a single data object. This object is passed to the **Financial Report Generator**, a final LangChain node that acts as a professional analyst. Using the merged data (company details, score, verdict, etc.), it generates a polished, formatted HTML email body. Finally, a **Gmail** node sends this HTML report as an email to the specified recipient.\n\n---\n\n### Set up steps\n\n1.  **Configure Credentials**:\n    - **OpenAI**: Set up an OpenAI API credential for the three language model nodes. Ensure it has access to the `gpt-5-mini` model.\n    - **Google Drive**: Configure OAuth2 credentials for the \"Upload audio\" node to allow file uploads.\n    - **Gmail**: Set up OAuth2 credentials for the \"Send report\" node.\n\n2.  **Configure Webhook**:\n    - Note the webhook ID and path. This URL must be configured in ElevenLabs to send post-call data to this n8n instance.\n\n3.  **Update Node Parameters**:\n    - **Google Drive**: Modify the \"Upload audio\" node if the target folder (`folderId`) is not the root.\n    - **Information Extractor**: The extraction attributes (company, name, address, VAT) are pre-configured. No changes are needed unless the target data fields change.\n    - **Gmail**: Update the **Gmail** node with the recipient email address (`xxx@xxx.com`) and verify the email subject line formatting.\n\n4.  **Activate Workflow**: Once all credentials and parameters are set, toggle the workflow from `active: false` to `active: true` in the n8n editor to start listening for webhook calls.\n\n---\n\n👉 [Subscribe to my new **YouTube channel**](https://youtube.com/@n3witalia). Here I’ll share videos and Shorts with practical tutorials and **FREE templates for n8n**.\n\n[![image](https://n3wstorage.b-cdn.net/n3witalia/youtube-n8n-cover.jpg)](https://youtube.com/@n3witalia)\n\n\n---\n\n### **Need help customizing?**  \n[Contact me](mailto:info@n3w.it) for consulting and support or add me on [Linkedin](https://www.linkedin.com/in/davideboizza/).","workflow":{"id":"Yubcg4N0YtRu2Ctg","meta":{"instanceId":"a4bfc93e975ca233ac45ed7c9227d84cf5a2329310525917adaf3312e10d5462","templateCredsSetupCompleted":true},"name":"Financial Report from ElevenLabs Interview","tags":[],"nodes":[{"id":"18d4a836-4eca-4447-910f-84aeae98a106","name":"Webhook","type":"n8n-nodes-base.webhook","notes":"wsec_0878db4550c39a8cac0049c8ad5c7b8f8a8072381ba13f6a7f4c522496bb62e0","position":[-704,176],"webhookId":"0a1e32dd-fb2d-450f-a9bd-e69c43bfdecf","parameters":{"path":"0a1e32dd-fb2d-450f-a9bd-e69c43bfdecf","options":{},"httpMethod":"POST"},"typeVersion":2.1},{"id":"3ffd9b5f-7c36-43d2-ba76-4c8773561ead","name":"Switch","type":"n8n-nodes-base.switch","position":[-416,176],"parameters":{"rules":{"values":[{"outputKey":"Post Call Audio","conditions":{"options":{"version":3,"leftValue":"","caseSensitive":true,"typeValidation":"loose"},"combinator":"and","conditions":[{"id":"cd1ad04f-645e-4fe6-b543-be60c2cd16f0","operator":{"type":"string","operation":"equals"},"leftValue":"={{ $json.body.type }}","rightValue":"post_call_audio"}]},"renameOutput":true},{"outputKey":"Post call Transcription","conditions":{"options":{"version":3,"leftValue":"","caseSensitive":true,"typeValidation":"loose"},"combinator":"and","conditions":[{"id":"4d4adf79-02f3-4647-919b-3a6c96a692f1","operator":{"name":"filter.operator.equals","type":"string","operation":"equals"},"leftValue":"={{ $json.body.type }}","rightValue":"post_call_transcription"}]},"renameOutput":true}]},"options":{},"looseTypeValidation":true},"typeVersion":3.4},{"id":"f7a27d9f-b89f-498e-bb48-cc540371b33f","name":"OpenAI Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[672,656],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-5-mini","cachedResultName":"gpt-5-mini"},"options":{},"builtInTools":{}},"credentials":{"openAiApi":{"id":"TefveNaDaMERl1hY","name":"OpenAi account (Eure)"}},"typeVersion":1.3},{"id":"4db2c641-9db8-4fe7-82c5-7531e0450a4f","name":"Upload audio","type":"n8n-nodes-base.googleDrive","position":[224,0],"parameters":{"name":"={{$binary.data.fileName}}","driveId":{"__rl":true,"mode":"list","value":"My Drive"},"options":{},"folderId":{"__rl":true,"mode":"list","value":"root","cachedResultName":"/ (Root folder)"}},"credentials":{"googleDriveOAuth2Api":{"id":"HEy5EuZkgPZVEa9w","name":"Google Drive account (n3w.it)"}},"typeVersion":3},{"id":"e9ba23bb-a474-4d6e-8905-7b9c77b2d647","name":"Generate MP3","type":"n8n-nodes-base.code","position":[0,0],"parameters":{"jsCode":"// Estrai il Base64 audio\nconst base64Audio = $input.item.json.body.data.full_audio;\nconst conversationId = $input.item.json.body.data.conversation_id;\n\n// Converti Base64 in Buffer binario\nconst audioBuffer = Buffer.from(base64Audio, 'base64');\n\nreturn {\n  json: {\n    conversation_id: conversationId,\n    agent_id: $input.item.json.body.data.agent_id,\n    agent_name: $input.item.json.body.data.agent_name,\n    user_id: $input.item.json.body.data.user_id\n  },\n  binary: {\n    data: {\n      data: audioBuffer.toString('base64'),\n      mimeType: 'audio/mpeg',\n      fileName: `conversation_${conversationId}.mp3`\n    }\n  }\n};"},"typeVersion":2},{"id":"9b269611-df30-4ad4-b1e6-2c738c4c97bf","name":"Get Transcript","type":"n8n-nodes-base.set","position":[-16,320],"parameters":{"options":{},"assignments":{"assignments":[{"id":"996c3a65-c82f-4756-8b87-e8a46366cd2b","name":"transcript","type":"array","value":"={{ $json.body.data.transcript }}"}]}},"typeVersion":3.4},{"id":"c6361b06-59ef-42a8-980b-e07857f39567","name":"Extract Fulltext","type":"n8n-nodes-base.code","position":[224,320],"parameters":{"jsCode":"const transcript = $json.transcript;\n\nconst fullText = transcript\n  .filter(item => item.message) // esclude null\n  .map(item => `${item.role}: ${item.message}`)\n  .join('\\n\\n');\n\nreturn [\n  {\n    json: {\n      conversation_id: $json.conversation_id,\n      agent_name: $json.agent_name,\n      transcript_text: fullText\n    }\n  }\n];\n"},"typeVersion":2},{"id":"de7c5325-69a7-49e8-80c6-d3846d9d25ec","name":"Calculate Rating","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[736,480],"parameters":{"text":"={{ $json.transcript_text }}","batching":{},"messages":{"messageValues":[{"message":"=**# QUANTITATIVE EVALUATION SYSTEM**\n\nYou are a **financial and management analysis agent**. You receive as input the text of an interview. Your task is to analyze the responses and produce a **complete quantitative evaluation** according to the methodology described below.\n\n---\n\n## INPUT\n\nThe interview text will be provided to you as a conversation. Analyze **exclusively the content of the interviewee’s responses**.\n\n---\n\n## PHASE 1 – EVALUATION OF THE MACRO-AREAS (scale 1–5)\n\nEvaluate each of the **8 macro-areas** by assigning a score from **1 to 5** according to the following criteria:\n\n| Score | Meaning                                 |\n| ----- | --------------------------------------- |\n| 1     | Structural absence or lack of awareness |\n| 2     | Reactive or superficial management      |\n| 3     | Partial or intermittent structure       |\n| 4     | Stable and conscious structure          |\n| 5     | Integrated and anticipatory structure   |\n\n**Base each score on:**\n\n* Presence of concrete examples in the responses\n* Internal consistency among the responses\n* Ability to connect decisions with consequences\n* Level of demonstrated economic and financial awareness\n\n---\n\n## OUTPUT\n\n**FINAL VERDICT: [POSITIVE / NEUTRAL / NEGATIVE]**\nRisk classification: [Low risk / Medium behavioral risk / High behavioral risk]\n\nReturn a valid JSON object with the following structure:\n\n{\n  \"score\": <number>,\n  \"verdict\": \"<string>\",\n  \"reason\": \"<string>\"\n}\n\nDo not include any text, explanation, or markdown outside the JSON object.\n"}]},"promptType":"define","hasOutputParser":true},"typeVersion":1.9},{"id":"83d64adc-c283-4c6a-be08-b3de5794f7fb","name":"Structured Output Parser","type":"@n8n/n8n-nodes-langchain.outputParserStructured","position":[960,672],"parameters":{"schemaType":"manual","inputSchema":"{\n\t\"type\": \"object\",\n\t\"properties\": {\n\t\t\"score\": {\n\t\t\t\"type\": \"number\"\n\t\t},\n\t\t\"verdict\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n      \"reason\": {\n\t\t\t\"type\": \"string\"\n\t\t}\n\t}\n}"},"typeVersion":1.3},{"id":"decaad9a-3112-49fe-baac-7eea6b1062ec","name":"Information Extractor","type":"@n8n/n8n-nodes-langchain.informationExtractor","position":[736,144],"parameters":{"text":"={{ $json.transcript_text }}","options":{"systemPromptTemplate":"You are an expert extraction algorithm.\nOnly extract relevant information from the text.\nIf you do not know the value of an attribute asked to extract, you may omit the attribute's value."},"attributes":{"attributes":[{"name":"company_name","required":true,"description":"Comany name"},{"name":"name","required":true,"description":"Name about the CEO"},{"name":"address","required":true,"description":"Complete address"},{"name":"vat_number","required":true,"description":"VAT number"}]}},"typeVersion":1.2},{"id":"cb1cc836-6eec-46a9-91e1-0e96cd3aef52","name":"OpenAI Chat Model1","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[704,320],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-5-mini","cachedResultName":"gpt-5-mini"},"options":{},"builtInTools":{}},"credentials":{"openAiApi":{"id":"TefveNaDaMERl1hY","name":"OpenAi account (Eure)"}},"typeVersion":1.3},{"id":"d3141c0e-076a-4e2b-af99-e5f138db1c70","name":"OpenAI Chat Model2","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[1472,480],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-5-mini","cachedResultName":"gpt-5-mini"},"options":{},"builtInTools":{}},"credentials":{"openAiApi":{"id":"TefveNaDaMERl1hY","name":"OpenAi account (Eure)"}},"typeVersion":1.3},{"id":"b66c2bbc-3a2a-4be7-a7fc-ce5ca286b793","name":"Merge","type":"n8n-nodes-base.merge","position":[1232,304],"parameters":{"mode":"combine","options":{},"combineBy":"combineAll"},"typeVersion":3.2},{"id":"4ce4f456-223e-48d6-a889-fd5924d5b92f","name":"Financial Report Generator","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[1488,304],"parameters":{"text":"=Company: {{ $json.output.company_name }}\nName: {{ $json.output.name }}\nAddress {{ $json.output.address }}\nVAT Number: {{ $json.output.vat_number }}\nScore: {{ $json.output.score }}\nVerdict: {{ $json.output.verdict }}\nReason: {{ $json.output.reason }}","batching":{},"messages":{"messageValues":[{"message":"=# FINANCIAL REPORT GENERATOR\n\n## Role\nYou are a professional financial analyst assistant. Your job is to generate a concise, structured financial risk report as an HTML email body based on the provided company data and credit assessment results.\n\n---\n\n## Input you will receive\n- **Company**: legal company name\n- **Name**: contact or representative name\n- **Address**: registered company address\n- **VAT Number**: company VAT identifier\n- **Score**: numerical credit/risk score\n- **Verdict**: overall assessment result (e.g., POSITIVE, NEUTRAL, NEGATIVE)\n- **Reason**: explanation behind the verdict\n\n---\n\n## Your task\nGenerate a formal financial report formatted as an HTML email body that:\n- Uses inline CSS only (no external stylesheets, no `<style>` blocks)\n- Is compatible with major email clients (Outlook, Gmail, Apple Mail)\n- Presents information in a clean, professional layout using tables\n- Uses a neutral color palette suitable for a financial document\n\n---\n\n## HTML structure\n\n1. **Header** — company name and report title, light gray background\n2. **Company Details** — two-column table: label on the left, value on the right\n3. **Risk Assessment Summary** — score and verdict displayed prominently, with a colored badge:\n   - POSITIVE → green (`#2e7d32`)\n   - NEUTRAL → orange (`#e65100`)\n   - NEGATIVE → red (`#c62828`)\n4. **Assessment Rationale** — plain prose paragraph expanding the reason field\n5. **Recommendation** — one short paragraph with suggested course of action based on the verdict\n6. **Footer** — small gray text: \"This report was automatically generated.\"\n\n---\n\n## Hard constraints\n- Output ONLY the HTML code, nothing else — no explanations, no markdown, no code fences\n- Use only inline CSS\n- Never add financial data or assumptions not present in the input\n- The output must be a complete HTML fragment starting with `<div>` (not a full `<html>` document)"}]},"promptType":"define"},"typeVersion":1.9},{"id":"84d37d8c-293d-4766-b451-f365a6c33c3a","name":"Send report","type":"n8n-nodes-base.gmail","position":[1856,304],"webhookId":"3458fe68-6aca-454e-ba61-eb7591980705","parameters":{"sendTo":"xxx@xxx.com","message":"={{ $json.text }}","options":{},"subject":"=[Financial Report] {{ $('Merge').item.json.output.company_name }}"},"credentials":{"gmailOAuth2":{"id":"nyuHvSX5HuqfMPlW","name":"Gmail account (n3w.it)"}},"typeVersion":2.2},{"id":"238f24be-3071-4830-8b8f-9974886059b5","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-832,-640],"parameters":{"width":1296,"height":480,"content":"## Financial Risk Report Generator from ElevenLabs Interview audio Using AI\nThis workflow automates the process of receiving a post-call audio file and transcription from [ElevenLabs](https://try.elevenlabs.io/ahkbf00hocnu), processing them, and generating a financial risk report.\n\n### How it works\n\nThis workflow receives ElevenLabs webhook events and routes them by payload type to handle either post-call audio or post-call transcription. Audio events are decoded from Base64, converted into an MP3 binary file, and uploaded to Google Drive for storage and traceability. Transcription events are transformed into a single readable conversation text, which is then analyzed in parallel by AI nodes: one extracts structured company details, and another assigns a financial risk score, verdict, and justification using structured JSON output.\n\nThe extracted company data and risk evaluation are merged and passed to a final report-generation step. That node creates a polished HTML financial risk report, which is then sent automatically by Gmail to the target recipient. The result is a fully automated pipeline from interview output to stakeholder-ready email delivery.\n\n### Setup steps\n\nConfigure the required credentials first: OpenAI for the language model nodes, Google Drive for audio upload, and Gmail for sending the final report. Then verify the webhook path and ID, and register that endpoint in ElevenLabs so post-call audio and transcription events are sent into the workflow correctly.\n\nNext, review node-specific parameters. Update the Google Drive destination folder if needed, confirm the extraction fields still match the business data you want to collect, and replace the placeholder Gmail recipient with the correct email address while checking the subject format. After credentials and node settings are validated, activate the workflow in n8n so it can start receiving webhook events and processing interviews automatically.\n"},"typeVersion":1},{"id":"c29ee6f8-8765-47cd-b903-b5bb317e56a8","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[-48,-112],"parameters":{"color":7,"width":512,"height":288,"content":"## STEP 1 - Upload audio\nSave audio call to Google Drive"},"typeVersion":1},{"id":"044d60e0-933a-4b81-a1d1-859340c9b3f3","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-48,224],"parameters":{"color":7,"width":512,"height":320,"content":"## STEP 2 - Get Audio Transcript\nGet audio transcript from Elevenlabs audio"},"typeVersion":1},{"id":"018f39de-eb8e-4b68-bf06-db89044a8028","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[512,16],"parameters":{"color":7,"width":608,"height":800,"content":"## STEP 3 - Extract Informations\nThe full transcript text is then used by two nodes in parallel: Information Extractor and Calculate Rating"},"typeVersion":1},{"id":"b40b0a21-70a6-4621-9188-489f71613228","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[1392,144],"parameters":{"color":7,"width":672,"height":496,"content":"## STEP 4 - Financial Report\nFinancial Report Generator and send it to email"},"typeVersion":1},{"id":"6281f67e-6000-4978-abb6-c1fe3900c40d","name":"Sticky Note9","type":"n8n-nodes-base.stickyNote","position":[512,-896],"parameters":{"color":7,"width":736,"height":736,"content":"## MY NEW YOUTUBE CHANNEL\n👉 [Subscribe to my new **YouTube channel**](https://youtube.com/@n3witalia). Here I’ll share videos and Shorts with practical tutorials and **FREE templates for n8n**.\n\n[![image](https://n3wstorage.b-cdn.net/n3witalia/youtube-n8n-cover.jpg)](https://youtube.com/@n3witalia)"},"typeVersion":1}],"active":false,"pinData":{},"settings":{"binaryMode":"separate","availableInMCP":false,"executionOrder":"v1"},"versionId":"80c53f08-28ed-4582-82e7-5f185d7e887e","connections":{"Merge":{"main":[[{"node":"Financial Report Generator","type":"main","index":0}]]},"Switch":{"main":[[{"node":"Generate MP3","type":"main","index":0}],[{"node":"Get Transcript","type":"main","index":0}]]},"Webhook":{"main":[[{"node":"Switch","type":"main","index":0}]]},"Generate MP3":{"main":[[{"node":"Upload audio","type":"main","index":0}]]},"Get Transcript":{"main":[[{"node":"Extract Fulltext","type":"main","index":0}]]},"Calculate Rating":{"main":[[{"node":"Merge","type":"main","index":1}]]},"Extract Fulltext":{"main":[[{"node":"Information Extractor","type":"main","index":0},{"node":"Calculate Rating","type":"main","index":0}]]},"OpenAI Chat Model":{"ai_languageModel":[[{"node":"Calculate Rating","type":"ai_languageModel","index":0}]]},"OpenAI Chat Model1":{"ai_languageModel":[[{"node":"Information Extractor","type":"ai_languageModel","index":0}]]},"OpenAI Chat Model2":{"ai_languageModel":[[{"node":"Financial Report Generator","type":"ai_languageModel","index":0}]]},"Information Extractor":{"main":[[{"node":"Merge","type":"main","index":0}]]},"Structured Output Parser":{"ai_outputParser":[[{"node":"Calculate Rating","type":"ai_outputParser","index":0}]]},"Financial Report Generator":{"main":[[{"node":"Send report","type":"main","index":0}]]}}},"lastUpdatedBy":29,"workflowInfo":{"nodeCount":21,"nodeTypes":{"n8n-nodes-base.set":{"count":1},"n8n-nodes-base.code":{"count":2},"n8n-nodes-base.gmail":{"count":1},"n8n-nodes-base.merge":{"count":1},"n8n-nodes-base.switch":{"count":1},"n8n-nodes-base.webhook":{"count":1},"n8n-nodes-base.stickyNote":{"count":6},"n8n-nodes-base.googleDrive":{"count":1},"@n8n/n8n-nodes-langchain.chainLlm":{"count":2},"@n8n/n8n-nodes-langchain.lmChatOpenAi":{"count":3},"@n8n/n8n-nodes-langchain.informationExtractor":{"count":1},"@n8n/n8n-nodes-langchain.outputParserStructured":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"Davide Boizza","username":"n3witalia","bio":"Full-stack Web Developer based in Italy specialising in Marketing & AI-powered automations. 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