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Summary
Turns a plain name + email into a fully-enriched HubSpot contact by matching the person in Apollo, pulling their latest LinkedIn activity, summarising the findings with GPT-4o, and upserting the clean data into HubSpot
Key use-cases
SDRs enriching inbound demo requests before routing
RevOps teams keeping executive records fresh
Marketers building highly-segmented email audiences
Inputs
| Field | Type | Example |
|---|---|---|
| name | string | “Jane Doe” |
| string | “[email protected]” |
Required credentials
| Service | Node | Notes |
|---|---|---|
| Apollo.io API key | HTTP Request – “Enrich with Apollo” | Set in header x-api-key |
| RapidAPI key | (Fresh-LinkedIn-Profile-Data) “Get recent posts” | Header x-rapidapi-key |
| OpenAI 3 LangChain nodes | Supply an API key | default model gpt-4o-mini |
| HubSpot OAuth2 | “Enrich in HubSpot” | Add/create any custom contact properties referenced |
High-level flow
Trigger – Runs when another workflow passes name & email.
Clean – JS Code node normalises & deduplicates emails.
Apollo match – Queries /people/match; skips if no person.
LinkedIn fetch – Grabs up to 3 original posts from last 30 days.
AI summary chain
OpenAI → Structured/Auto-fixing parsers
Produces a strict JSON block with job title, location, summaries, etc.
HubSpot upsert – Maps every key (plus five custom properties) into the contact record.
Sticky-notes annotate the canvas; error-prone bits have retry logic.