{ "format": "revenanas.clay-workflow/v1", "name": "Revenanas Library - Closed-Won Lookalikes with Tender Signal", "slug": "clay-closed-won-lookalikes-tender-signal", "description": "Pull why-we-won context and closed-lost suppressions from HubSpot, find ten lookalikes, retrieve official tender evidence with Perplexity, qualify each account with a Claygent, and write every decision to Clay Audiences.", "source": { "builder": "Clay official Terracotta CLI", "workspace_type": "Revenanas enterprise test", "workflow_id": "wf_0tlthl7tJ2NzZgftGyQ", "exported": "2026-09-25", "last_tested": "2026-09-23", "published": false }, "verification": { "graph_valid": true, "passing_run_ids": [ "wfr_0tltj9vvkzV6QAFfY2N", "wfr_0tltnxfsfeWrAERcScm" ], "changes_from_tested_build": [] }, "requires": [ "HubSpot connected in Clay; company properties for why-we-won, winning signal, MEDDPICC, signal keywords, Clay domain and segment status (the demo uses demo_vanta_* names).", "Perplexity action available in Clay.", "Ten Clay Audiences company fields, passed with --set audf_*=." ], "trigger": { "key": "trigger", "spec": { "triggerType": "manual", "inputSchema": { "type": "object", "properties": {} } } }, "nodes": [ { "key": "pull_closed_won_why_we_won_context_from_hubspot", "spec": { "name": "Pull closed-won why-we-won context from HubSpot", "description": "Looks up the synthetic closed-won seed companies and their demo win-context fields directly from HubSpot.", "nodeType": "tool", "tools": [ { "toolType": "clay_action", "actionKey": "hubspot-lookup-object", "actionPackageId": "a2584689-b965-4a25-847d-17b7abcddca3", "appAccountName": "Jack- Test ", "inputMappingConfig": { "limit": { "type": "static", "value": 10 }, "objectTypeId": { "type": "static", "value": "0-2" }, "removeBlankValues": { "type": "static", "value": true }, "fields|fieldsToFilterBy": { "type": "static", "value": [ "demo_vanta_segment_status" ] }, "fields|demo_vanta_segment_status": { "type": "static", "value": "closed_won_seed" } } } ], "incomingEdges": [ { "sourceNode": "{{trigger}}" } ] } }, { "key": "pull_closed_lost_suppressions_from_hubspot", "spec": { "name": "Pull closed-lost suppressions from HubSpot", "description": "Looks up synthetic closed-lost companies so they can be excluded from activation.", "nodeType": "tool", "tools": [ { "toolType": "clay_action", "actionKey": "hubspot-lookup-object", "actionPackageId": "a2584689-b965-4a25-847d-17b7abcddca3", "appAccountName": "Jack- Test ", "inputMappingConfig": { "limit": { "type": "static", "value": 20 }, "objectTypeId": { "type": "static", "value": "0-2" }, "removeBlankValues": { "type": "static", "value": true }, "fields|fieldsToFilterBy": { "type": "static", "value": [ "demo_vanta_segment_status" ] }, "fields|demo_vanta_segment_status": { "type": "static", "value": "closed_lost_suppression" } } } ], "incomingEdges": [ { "sourceNode": "{{pull_closed_won_why_we_won_context_from_hubspot}}" } ] } }, { "key": "derive_icp_and_signal_pattern_from_hubspot_wins", "spec": { "name": "Derive ICP and signal pattern from HubSpot wins", "description": "Aggregates seed domains, why-we-won narratives, MEDDPICC context, signal keywords, and closed-lost suppressions from the live HubSpot lookup results.", "nodeType": "code", "inputSchema": { "type": "object", "properties": { "closed_won_results": { "type": "array", "items": { "type": "object" }, "sourceNodeId": "{{pull_closed_won_why_we_won_context_from_hubspot}}", "sourcePath": "$.result.results" }, "closed_lost_results": { "type": "array", "items": { "type": "object" }, "sourceNodeId": "{{pull_closed_lost_suppressions_from_hubspot}}", "sourcePath": "$.result.results" } } }, "outputSchema": { "seed_count": { "type": "number", "description": "Number of distinct closed-won seed domains pulled from HubSpot." }, "why_we_won": { "type": "string", "description": "Combined why-we-won narratives taken directly from the matched HubSpot company properties." }, "seed_domains": { "type": "string", "description": "Comma-separated demo Clay domains from the closed-won HubSpot records." }, "winning_signal": { "type": "string", "description": "Distinct winning-signal values taken directly from HubSpot." }, "meddpic_context": { "type": "string", "description": "Combined MEDDPICC context taken directly from HubSpot." }, "signal_keywords": { "type": "string", "description": "Signal-search keywords taken directly from HubSpot." }, "suppression_domains": { "type": "string", "description": "Comma-separated closed-lost domains pulled from HubSpot." }, "hubspot_segment_name": { "type": "string", "description": "The HubSpot segment represented by the live lookup." }, "hubspot_source_record_ids": { "type": "string", "description": "JSON list of HubSpot company IDs that produced the pattern." } }, "code": "import json\n\n\ndef _properties(rows):\n for row in rows or []:\n properties = row.get(\"properties\") or {}\n if properties:\n yield properties\n\n\ndef _unique(values):\n seen = set()\n result = []\n for value in values:\n value = str(value or \"\").strip()\n if value and value not in seen:\n seen.add(value)\n result.append(value)\n return result\n\n\ndef handler(context):\n won_rows = context.get_input(\"closed_won_results\") or []\n lost_rows = context.get_input(\"closed_lost_results\") or []\n won = list(_properties(won_rows))\n lost = list(_properties(lost_rows))\n\n seed_domains = _unique(row.get(\"demo_vanta_clay_domain\") for row in won)\n why_we_won = _unique(row.get(\"demo_vanta_why_we_won\") for row in won)\n winning_signals = _unique(row.get(\"demo_vanta_winning_signal\") for row in won)\n signal_keywords = _unique(row.get(\"demo_vanta_signal_keywords\") for row in won)\n meddpic = _unique(row.get(\"demo_vanta_meddpic_summary\") for row in won)\n suppressions = _unique(row.get(\"demo_vanta_clay_domain\") for row in lost)\n\n return {\n \"hubspot_segment_name\": \"[DEMO] Vanta — Closed-Won Seeds | Public Tender Signal\",\n \"seed_count\": len(seed_domains),\n \"seed_domains\": \",\".join(seed_domains),\n \"why_we_won\": \"\\n\".join(f\"- {value}\" for value in why_we_won),\n \"winning_signal\": \", \".join(winning_signals),\n \"signal_keywords\": \", \".join(signal_keywords),\n \"meddpic_context\": \"\\n\".join(f\"- {value}\" for value in meddpic),\n \"suppression_domains\": \",\".join(suppressions),\n \"hubspot_source_record_ids\": json.dumps(\n [row.get(\"id\") for row in won_rows if row.get(\"id\")],\n separators=(\",\", \":\"),\n ),\n }\n", "incomingEdges": [ { "sourceNode": "{{pull_closed_lost_suppressions_from_hubspot}}" } ] } }, { "key": "find_10_lookalikes_from_hubspot_seed_domains", "spec": { "name": "Find 10 lookalikes from HubSpot seed domains", "description": "Finds ten European HR-technology lookalikes using the seed domains derived from the HubSpot closed-won records.", "nodeType": "tool", "tools": [ { "toolType": "clay_action", "actionKey": "find-company-lookalikes-v2", "actionPackageId": "e251a70e-46d7-4f3a-b3ef-a211ad3d8bd2", "inputMappingConfig": { "limit": { "type": "static", "value": 10 }, "country_names": { "type": "static", "value": [ "United Kingdom", "France", "Germany", "Netherlands", "Ireland", "Sweden", "Denmark", "Finland", "Norway", "Belgium", "Spain", "Portugal", "Estonia" ] }, "company_identifier": { "type": "reference", "expression": "{{seed_domains}}" }, "has_resolved_domain": { "type": "static", "value": true }, "maximum_member_count": { "type": "static", "value": 2000 }, "minimum_member_count": { "type": "static", "value": 50 }, "resolved_domain_is_live": { "type": "static", "value": true } } } ], "inputSchema": { "type": "object", "properties": { "seed_domains": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.seed_domains" } } }, "incomingEdges": [ { "sourceNode": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}" } ] } }, { "key": "research_official_tender_evidence_for_every_look", "spec": { "name": "Research official tender evidence for every lookalike", "description": "Runs once per lookalike and searches the web for official procurement evidence with citations.", "nodeType": "tool", "tools": [ { "toolType": "clay_action", "actionKey": "perplexity-chat-completions", "actionPackageId": "69474dbc-6175-41b6-b619-40630a5870b6", "inputMappingConfig": { "model": { "type": "static", "value": "sonar" }, "prompt": { "type": "reference", "expression": "Begin your answer with this exact identity header, preserving both values even when no evidence is found: COMPANY: {{__item.name}} | DOMAIN: {{__item.domain}}. Then find the strongest official public procurement notice involving that exact company as a supplier, award winner, incumbent, framework participant, or named bidder. Search for exact and legal-name variants. Prioritize a recent or still-active contract award, extension, framework appointment, or tender. Return the direct official notice URL and quote only facts shown by that source: supplier legal name, contracting authority, notice title, notice or award date, contract term, and value. If no exact supplier match exists, keep the identity header and state NO VERIFIED OFFICIAL NOTICE. Do not use vendor marketing pages or procurement portal home/search pages as evidence." }, "systemPrompt": { "type": "static", "value": "You are a cautious procurement researcher. Use only official government procurement sources. Never infer an award or supplier identity from weak evidence and never fabricate URLs or contract details." }, "searchDomainFilter": { "type": "static", "value": "find-tender.service.gov.uk,contractsfinder.service.gov.uk,ted.europa.eu" } } } ], "listMode": true, "listFailureMode": "fail_at_end", "listEntriesRef": { "path": "$.result.companies", "sourceNodeId": "{{find_10_lookalikes_from_hubspot_seed_domains}}" }, "incomingEdges": [ { "sourceNode": "{{find_10_lookalikes_from_hubspot_seed_domains}}" } ] } }, { "key": "join_lookalikes_searches_and_hubspot_win_context", "spec": { "name": "Join lookalikes, searches, and HubSpot win context", "description": "Creates one self-contained Claygent research item for every lookalike and marks HubSpot closed-lost suppressions.", "nodeType": "code", "inputSchema": { "type": "object", "properties": { "companies": { "type": "array", "items": { "type": "object" }, "sourceNodeId": "{{find_10_lookalikes_from_hubspot_seed_domains}}", "sourcePath": "$.result.companies" }, "why_we_won": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.why_we_won" }, "search_results": { "type": "array", "items": { "type": "object" }, "sourceNodeId": "{{research_official_tender_evidence_for_every_look}}", "sourcePath": "$.results" }, "winning_signal": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.winning_signal" }, "meddpic_context": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.meddpic_context" }, "signal_keywords": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.signal_keywords" }, "suppression_domains": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.suppression_domains" } } }, "outputSchema": { "research_items": { "type": "string", "description": "Array of lookalike research items enriched with Google results and the inherited HubSpot context." }, "lookalike_count": { "type": "number", "description": "Number of lookalike companies sent to the Claygent." }, "suppression_count": { "type": "number", "description": "Number of lookalikes suppressed by the HubSpot closed-lost set." } }, "code": "import json\n\n\ndef _split_domains(value):\n return {\n part.strip().lower()\n for part in str(value or \"\").split(\",\")\n if part.strip()\n }\n\n\ndef handler(context):\n companies = context.get_input(\"companies\") or []\n searches = context.get_input(\"search_results\") or []\n suppressions = _split_domains(context.get_input(\"suppression_domains\"))\n\n items = []\n for index, company in enumerate(companies):\n domain = str(company.get(\"domain\") or \"\").lower().strip()\n search = searches[index] if index < len(searches) else {}\n items.append(\n {\n \"company_name\": company.get(\"name\") or company.get(\"company_name\") or domain,\n \"domain\": domain,\n \"linkedin_url\": company.get(\"linkedin_url\") or \"\",\n \"lookalike_description\": company.get(\"description\") or \"\",\n \"is_hubspot_suppressed\": domain in suppressions,\n \"search_query_url\": search.get(\"link_to_google_search\") or \"\",\n \"search_results_json\": json.dumps(\n search.get(\"search_results\") or [],\n ensure_ascii=False,\n separators=(\",\", \":\"),\n ),\n \"hubspot_why_we_won\": context.get_input(\"why_we_won\") or \"\",\n \"hubspot_winning_signal\": context.get_input(\"winning_signal\") or \"\",\n \"hubspot_signal_keywords\": context.get_input(\"signal_keywords\") or \"\",\n \"hubspot_meddpic_context\": context.get_input(\"meddpic_context\") or \"\",\n }\n )\n\n return {\n \"research_items\": json.dumps(items, ensure_ascii=False, separators=(\",\", \":\")),\n \"lookalike_count\": len(companies),\n \"suppression_count\": sum(1 for item in items if item[\"is_hubspot_suppressed\"]),\n }\n", "incomingEdges": [ { "sourceNode": "{{research_official_tender_evidence_for_every_look}}" } ] } }, { "key": "claygent_qualify_tender_signal_against_why_we_wo", "spec": { "name": "Claygent: qualify tender signal against why we won", "description": "Runs once per researched lookalike and decides whether cited official-source evidence matches the win pattern pulled from HubSpot.", "nodeType": "agent", "inputSchema": { "type": "object", "properties": { "why_we_won": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.why_we_won" }, "winning_signal": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.winning_signal" }, "signal_keywords": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.signal_keywords" }, "meddpic_context": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.meddpic_context" }, "suppression_domains": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.suppression_domains" } } }, "outputSchema": { "domain": { "type": "string", "description": "Copy the company domain from the current research item exactly." }, "signal_type": { "type": "string", "description": "The evidenced trigger type, such as contract award, contract extension, framework appointment, or tender notice; return None otherwise." }, "company_name": { "type": "string", "description": "Copy only the value between COMPANY: and | DOMAIN: in the identity header; never include the separator or domain." }, "evidence_url": { "type": "string", "description": "The direct official procurement notice URL from the supplied search results; leave blank when no qualifying source exists." }, "evidence_date": { "type": "string", "description": "The date shown in the supplied result in YYYY-MM-DD where possible, or Not stated." }, "contract_value": { "type": "string", "description": "The value shown in the supplied result, or Not stated." }, "signal_summary": { "type": "string", "description": "For Qualified records only: one buyer-safe sentence of at most 18 words naming the conversational brand and short tender or contract. Never expose sources, authorities, HubSpot, qualification logic, or win-pattern language." }, "confidence_score": { "type": "number", "description": "Score from 0 to 100 based on official-source quality, exact supplier identity, recency, and relevance." }, "qualification_reason": { "type": "string", "description": "One or two sentences explaining the decision without adding facts absent from the search evidence." }, "qualification_status": { "type": "string", "description": "Return exactly Qualified, Not qualified, Unclear, or Suppressed." }, "contracting_authority": { "type": "string", "description": "The public body named in the supplied official result, or Not stated." } }, "listMode": true, "listFailureMode": "ignore_errors", "listEntriesRef": { "path": "$.results", "sourceNodeId": "{{research_official_tender_evidence_for_every_look}}" }, "agentName": "[DEMO] Vanta Tender Signal Qualifier", "agentPrompt": "You are the qualification Claygent in a Vanta demo. Evaluate exactly one researched lookalike. WEB RESEARCH WITH CITATIONS: {{__item}}. HUBSPOT WHY WE WON (pulled earlier in this same workflow): {{why_we_won}}. HUBSPOT WINNING SIGNAL: {{winning_signal}}. HUBSPOT SIGNAL KEYWORDS: {{signal_keywords}}. HUBSPOT MEDDPICC CONTEXT: {{meddpic_context}}. HUBSPOT CLOSED-LOST SUPPRESSION DOMAINS: {{suppression_domains}}. The research item begins with the identity header COMPANY: | DOMAIN: . Set company_name to the normal conversational brand name between COMPANY: and | DOMAIN:. Remove legal suffixes such as LIMITED, LTD, PLC, GmbH, Inc., or LLC and avoid all-caps legal names. Set domain to only the text after DOMAIN:. Preserve both values for every decision, including no-result cases, and never replace either with Not stated. Return Suppressed if that domain is in the HubSpot suppression list. Otherwise return Qualified only when the supplied research cites a direct official government procurement notice and establishes this exact company as supplier, award winner, framework participant, or incumbent in a recent or active award, extension, or procurement. Do not qualify a procurement portal homepage, a generic search page, a vendor marketing page, a catalogue listing by itself, a payments register by itself, or an ambiguous same-name company. The signal must plausibly recreate the inherited win pattern: security, privacy, supplier assurance, or compliance evidence becomes relevant to winning or delivering the public contract. Never invent a URL, authority, date, value, or fact absent from the supplied research. Keep qualification_reason for internal decision logic. For every Qualified result, signal_summary is outreach copy, not internal analysis: write one natural sentence of at most 18 words in the form ' won the tender' or ' extended its public-sector contract'. Use the conversational brand, retain the recognisable tender or service name, and end with a period. Do not mention the contracting authority, procurement board, official notice, source, citation, HubSpot, Vanta, lookalikes, alignment, qualification, the win pattern, compliance implications, dates, or contract value in signal_summary. If the research is promising but does not establish supplier identity or official notice details, return Unclear. If no official result supports it, return Not qualified.", "agentModel": "gpt-5.4-nano", "incomingEdges": [ { "sourceNode": "{{research_official_tender_evidence_for_every_look}}" } ] } }, { "key": "write_claygent_decisions_to_clay_audiences", "spec": { "name": "Write Claygent decisions to Clay Audiences", "description": "Upserts every researched lookalike by domain and stores its Claygent qualification, official evidence, confidence, and inherited HubSpot why-we-won context.", "nodeType": "tool", "tools": [ { "toolType": "clay_action", "actionKey": "upsert-audiences-record", "actionPackageId": "b1ab3d5d-b0db-4b30-9251-3f32d8b103c1", "inputMappingConfig": { "entityType": { "type": "static", "value": "ACCOUNT" }, "lookupFields|domain": { "type": "item", "path": "$.domain" }, "recordFields|org_name": { "type": "item", "path": "$.company_name" }, "recordFields|removeNullValues": { "type": "static", "value": true }, "lookupFields|selectedLookupFields": { "type": "static", "value": [ "domain" ] }, "recordFields|selectedRecordFields": { "type": "static", "value": [ "org_name", "{{set:audf_batch}}", "{{set:audf_why_we_won}}", "{{set:audf_qualification_status}}", "{{set:audf_signal_type}}", "{{set:audf_signal_summary}}", "{{set:audf_evidence_url}}", "{{set:audf_evidence_date}}", "{{set:audf_contract_value}}", "{{set:audf_contracting_authority}}", "{{set:audf_confidence_score}}" ] }, "recordFields|{{set:audf_batch}}": { "type": "static", "value": "vanta_tender_demo_2026-09-23" }, "recordFields|{{set:audf_why_we_won}}": { "type": "reference", "expression": "{{why_we_won}}" }, "recordFields|{{set:audf_qualification_status}}": { "type": "item", "path": "$.qualification_status" }, "recordFields|{{set:audf_signal_type}}": { "type": "item", "path": "$.signal_type" }, "recordFields|{{set:audf_signal_summary}}": { "type": "item", "path": "$.signal_summary" }, "recordFields|{{set:audf_evidence_url}}": { "type": "item", "path": "$.evidence_url" }, "recordFields|{{set:audf_contract_value}}": { "type": "item", "path": "$.contract_value" }, "recordFields|{{set:audf_evidence_date}}": { "type": "item", "path": "$.evidence_date" }, "recordFields|{{set:audf_contracting_authority}}": { "type": "item", "path": "$.contracting_authority" }, "recordFields|{{set:audf_confidence_score}}": { "type": "item", "path": "$.confidence_score" } } } ], "inputSchema": { "type": "object", "properties": { "why_we_won": { "type": "string", "sourceNodeId": "{{derive_icp_and_signal_pattern_from_hubspot_wins}}", "sourcePath": "$.why_we_won" } } }, "listMode": true, "listFailureMode": "ignore_errors", "listEntriesRef": { "path": "$.results", "sourceNodeId": "{{claygent_qualify_tender_signal_against_why_we_wo}}" }, "incomingEdges": [ { "sourceNode": "{{claygent_qualify_tender_signal_against_why_we_wo}}" } ] } } ], "tests": [] }