{"workflow":{"id":12710,"name":"Enrich B2B leads for Attio CRM with Apollo, LinkedIn, news and GPT-4o","views":143,"recentViews":0,"totalViews":143,"createdAt":"2026-01-14T12:47:48.189Z","description":"# **B2B Lead Enrichment | Attio CRM**\n\nThis n8n template automates B2B lead research and enrichment for Attio CRM. It combines data from Apollo.io, LinkedIn scraping, and news sources with AI-powered analysis to generate actionable sales intelligence - turning hours of manual BDR research into minutes.\n\n## Who is this for?\n\n- Sales teams using Attio CRM who want to reduce time spent on lead research\n- BDRs/SDRs who need rich prospect context before outreach\n- Revenue operations teams looking to automate CRM enrichment at scale\n\n## What problem does this workflow solve?\n\nBefore reaching out to a prospect, sales reps typically spend 15-30 minutes researching company background, recent news, leadership team, and LinkedIn activity. This workflow automates that entire research process, freeing BDRs to focus on relationship building instead of data gathering.\n\n## How it works\n\n1. Trigger: Manually execute (adapt to webhook or form trigger for automation)\n2. Apollo Enrichment: Fetches comprehensive company data by domain\n3. Parallel Processing: Three branches run simultaneously:\n    - News articles → Tavily extraction → AI summary\n    - LinkedIn company page → Scrape Creators → AI summary\n    - Leadership search (with web search) → Apollo person lookup → LinkedIn profiles → AI summary\n4. Validation: An LLM Critic agent verifies all claims using web search\n5. Final Output: Lead Enrichment Agent generates a structured dossier\n6. CRM Sync: Updates Attio company and people records\n\n## Good to Know\n\nEstimated API Costs (per enrichment):\n   - Apollo.io: Varies by plan (credits-based)\n   - Scrape Creators: ~$0.01-0.05 per profile\n   - Tavily: ~$0.01 per extraction\n   - OpenAI GPT-4o: ~$0.10-0.30 depending on content length\n\nRate Limits: Leadership profiles are processed sequentially to respect API limits. For bulk enrichment, consider adding delays between executions.\n\n## Requirements\n\n- Apollo.io account with API access\n- Scrape Creators API key (for LinkedIn scraping)\n- Tavily API key (for article extraction)\n- OpenAI API key (GPT-4o model access)\n- Attio CRM account with API access\n\n## Setup\n\n1. Import the workflow into n8n\n2. Configure credentials for each service:\n  \t- Apollo API (HTTP Header Auth with x-api-key)\n  \t- Scrape Creators API\n  \t- Tavily API\n  \t- OpenAI API\n  \t- Attio API\n3. Add these custom fields to your Attio Companies object:\n  \t- positioning (text)\n  \t- conversation_points (text)\n  \t- leadership_conversations (text)\n     - enrichment_status (select with \"complete\" option)\n4. Test with a single domain before running at scale\n\n## Customizing this workflow\n\n   - Trigger: Replace manual trigger with a webhook (real-time enrichment on new leads) or schedule node (batch processing)\n   - AI Prompts: Adjust the system prompts in AI agents to match your industry or ideal customer profile\n   - Output Fields: Modify the final Code node to map to your specific Attio field structure\n   - News Timeframe: Change the 6-month lookback in Apollo:LatestNews to your preferred range\n   - Leadership Depth: Adjust the number of leadership profiles to enrich based on your needs\n\nMade by [www.fenrirlabs.nl](www.fenrirlabs.nl)","workflow":{"meta":{"templateCredsSetupCompleted":false},"name":"B2B Lead Enrichment - Attio CRM","nodes":[{"id":"92b8a366-d717-47c8-91ba-b6f0ed3df9cb","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-48,-400],"parameters":{"color":7,"width":592,"height":128,"content":"## Business Outcome\n- Reduce the time spent by BDRs researching and enriching CRM leads\n- Reinvest that time in cultivating and building relationships with clients\n\n"},"typeVersion":1},{"id":"e88a10c6-6379-4598-ac07-14a2c2caf541","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[560,-496],"parameters":{"color":7,"width":592,"height":224,"content":"## System Outcomes\n- BDRs need to have trust in the outputs\n- It has minimal % chance of creating poor future moments between BDRs & Leads\n- It achieves human equivalence of a BDR trying to *quickly* complete enrichment\n- Fall back systems that give it the optimal chance to enrich\n- Fall back and graceful error handling when services are down or information can't be collected\n\n"},"typeVersion":1},{"id":"40498cf0-6fbd-468f-9388-b1afbc5ee08e","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-48,-496],"parameters":{"color":7,"width":592,"height":80,"content":"# B2B Lead Enrichment in Attio CRM\n"},"typeVersion":1},{"id":"b91b3d2c-ae8f-41b0-9681-0af03803c21e","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[-48,-160],"parameters":{"color":7,"width":592,"height":144,"content":"### Direct Metric\n*Avg Time BDR Spent Enriching Leads*\n- Baseline: x hours per week \n- Target: x hours per week \n- Delta: x hours per week\n\n\n"},"typeVersion":1},{"id":"7b8475c1-6fc0-4d31-9f39-707f25ff9e8a","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[560,-160],"parameters":{"color":7,"width":592,"height":144,"content":"### Proxy / Lagging Metric\n*Delta Opportunities Won Post Implementation*\n*Avg Time BDR Spent Cultivating Leads*\n*Avg Deal Size Delta Post Implementation*\n\n\n"},"typeVersion":1},{"id":"9adf1c04-3ffd-4458-93be-393b4d4fa6fd","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[-48,-256],"parameters":{"color":7,"width":1200,"height":80,"content":"## What Does Success Look 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}}"}]}},"credentials":{"httpHeaderAuth":{"id":"{{APOLLO_API_CREDENTIAL_ID}}","name":"Apollo API"}},"typeVersion":4.3},{"id":"ba45bb11-71c2-499e-929f-990e81f31ce8","name":"Extract","type":"@tavily/n8n-nodes-tavily.tavily","onError":"continueRegularOutput","position":[2496,-224],"parameters":{"urls":["={{ $json.url }}"],"options":{},"resource":"extract"},"credentials":{"tavilyApi":{"id":"{{TAVILY_API_CREDENTIAL_ID}}","name":"Tavily API"}},"typeVersion":1},{"id":"e22c45c1-7063-4778-ae96-cf383b402540","name":"Split Out1","type":"n8n-nodes-base.splitOut","position":[2272,192],"parameters":{"options":{},"fieldToSplitOut":"posts"},"typeVersion":1},{"id":"34904ea7-1d70-4611-9d05-c28ce88f73ef","name":"Last 5 Posts","type":"n8n-nodes-base.limit","position":[2496,192],"parameters":{"maxItems":5},"typeVersion":1},{"id":"08961d3e-32d8-4177-ac05-48849ccd4fce","name":"Last 5 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}}"}]}},"typeVersion":3.4},{"id":"abfacb52-7969-448d-a664-3bac2f80d168","name":"LinkedIn Leadership Summary","type":"@n8n/n8n-nodes-langchain.agent","position":[3392,592],"parameters":{"text":"={{ $json.prompt }}","options":{"systemMessage":"=## Role\nYou are an expert LinkedIn data extraction agent, specialising in summarising data for CRM enrichment that will feed into another agent.\n\n## Goal\nDiscover key information about {{ $('SetFields').item.json.organization.name }} through recent activities of employees. Transform that information in key talking points for lead generation and enrichment\n\n## Rules / Guardrails\n- MUST only provide information that is relevant to {{ $('SetFields').item.json.organization.name }}"},"promptType":"define"},"typeVersion":3.1},{"id":"06ed6b6a-5971-451e-afe9-5f269522b86c","name":"LLM Critic","type":"@n8n/n8n-nodes-langchain.agent","position":[4400,192],"parameters":{"text":"=Company Name: {{ $('Apollo:EnrichCompany').item.json.organization.name }}\nDomain: {{ $('Apollo:EnrichCompany').item.json.organization.primary_domain }}\nResearch: {{ $json.data }}","options":{"systemMessage":"=## Role\nYou are an expert LLM-as-a-Judge who verifies information provided by other LLMs. Your role is to review the claims being made are factual as of {{ $now }}\n\n\n## Goal\nProvide an analysis and recommended updates to the claims made\n\n## Rules / Guardrails\n- MUST only provide team information that is relevant to {{ $('SetFields').item.json.organization.name 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person.linkedin_url.replace('http://', 'https://');\n    values.linkedin = [linkedinUrl];\n  }\n  \n  // Email addresses (skip if null or empty, trim whitespace)\n  if (person.email && person.email.trim()) {\n    values.email_addresses = [{\n      email_address: person.email.trim()\n    }];\n  }\n  \n  return {\n    json: {\n      data: {\n        values: values\n      }\n    }\n  };\n});\n"},"typeVersion":2},{"id":"14a7438b-e05b-4921-9dc4-2ea413f903cd","name":"Post Assert Body: Company","type":"n8n-nodes-base.code","position":[800,192],"parameters":{"jsCode":"// Code node to format for Attio\n\nconst items = $input.all();\n\n \n\nreturn items.map(item => {\n\n  const org = item.json;\n\n \n\n  // Build the values object\n\n  const values = {\n\n    name: [org.name || ''],\n\n    description: [org.short_description || ''],\n\n    linkedin: [org.linkedin_url || '']\n\n  };\n\n \n\n  // Only add domains if primary_domain exists and is not empty\n\n  if (org.primary_domain && 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Note6","type":"n8n-nodes-base.stickyNote","position":[1216,480],"parameters":{"color":7,"width":2448,"height":624,"content":"## Leadership Enrichment\n\n"},"typeVersion":1},{"id":"3dac72b3-2dae-4c7c-a05b-174f15d1e782","name":"Sticky Note7","type":"n8n-nodes-base.stickyNote","position":[1600,64],"parameters":{"color":7,"width":2064,"height":368,"content":"## LinkedIn Company Enrichment\n\n"},"typeVersion":1},{"id":"f10d73e3-a673-416f-900b-478e1ca12750","name":"Sticky Note8","type":"n8n-nodes-base.stickyNote","position":[1600,-336],"parameters":{"color":7,"width":2064,"height":368,"content":"## Latest News Enrichment\n\n"},"typeVersion":1},{"id":"226dc2eb-b37c-4b06-9eae-b23189f4c4dc","name":"OpenAI Chat Model3","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[4336,400],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-4o","cachedResultName":"gpt-4o"},"options":{},"builtInTools":{"webSearch":{"searchContextSize":"medium"}}},"credentials":{"openAiApi":{"id":"{{OPENAI_API_CREDENTIAL_ID}}","name":"OpenAI API"}},"typeVersion":1.3},{"id":"258a5ce3-abf0-41b9-b067-c0fa939d55a7","name":"Structured Output Parser1","type":"@n8n/n8n-nodes-langchain.outputParserStructured","position":[4608,400],"parameters":{"jsonSchemaExample":"{\n\t\"verification\": [\"verification1\", \"verification2\"],\n\t\"updates\": [\"updated1\", \"update2\"]\n}"},"typeVersion":1.3},{"id":"08dbb8ad-d062-46bd-9aea-d32898bb2bd2","name":"AI Agent","type":"@n8n/n8n-nodes-langchain.agent","position":[4752,192],"parameters":{"text":"=## Discovery Inputs\n{{ $('Edit Fields3').item.json.data }}\n\n\n## Critiques From LLM-as-Judge\n{{ $json.output.updates }}\n","options":{"systemMessage":"=## Role\nYou are a expert Lead Enrichment Agent who ingests research and critiques done by other LLMs to produce a profile of a prospect to be entered in Attio CRM. \n\n## Goal\nCreate a dossier of a company into the following components:\n\n- Current Positioning: Paragraph on how they are positioning themselves today\n- Key Conversation Points: 1 - 3 key points to engage a sales conversation with\n- Leaderships Conversations: Paragraph on what their leadership team is saying\n\n## Rules / Guardrails\n- MUST only use input provided"},"promptType":"define","hasOutputParser":true},"typeVersion":3.1},{"id":"9c2fae38-7d60-4153-be77-5a17cf4eb870","name":"Assert Record: Company1","type":"n8n-nodes-attio.attio","position":[5376,192],"parameters":{"data":"={{ $json.data }}","object":"companies","resource":"Records","operation":"PUT -v2-objects--object--records","matching_attribute":"domains"},"credentials":{"attioApi":{"id":"{{ATTIO_API_CREDENTIAL_ID}}","name":"Attio 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};\n\n});"},"typeVersion":2}],"pinData":{},"connections":{"If1":{"main":[[{"node":"SetFields","type":"main","index":0}],[]]},"Merge":{"main":[[{"node":"Aggregate3","type":"main","index":0}]]},"Think":{"ai_tool":[[{"node":"AI Agent","type":"ai_tool","index":0}]]},"Think1":{"ai_tool":[[{"node":"LLM Critic","type":"ai_tool","index":0}]]},"Extract":{"main":[[{"node":"Edit Fields2","type":"main","index":0}]]},"AI Agent":{"main":[[{"node":"Code in JavaScript","type":"main","index":0}]]},"Aggregate":{"main":[[{"node":"LLMHelper2","type":"main","index":0}]]},"LLMHelper":{"main":[[{"node":"Apollo Summary Agent","type":"main","index":0}]]},"SetFields":{"main":[[{"node":"Post Assert Body: Company","type":"main","index":0}]]},"Aggregate1":{"main":[[{"node":"LLMHelper1","type":"main","index":0}]]},"Aggregate2":{"main":[[{"node":"LLMHelper","type":"main","index":0}]]},"Aggregate3":{"main":[[{"node":"Edit Fields3","type":"main","index":0}]]},"LLM Critic":{"main":[[{"node":"AI 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