Find decision makers and published emails from company pages with Apify and OpenAI

Reads the team, about and leadership pages on the company domains you list through Apify and returns the named people with title, seniority, a confidence level and an email only when the company itself publishes one. Each person is scored by seniority and by how well the title matches the roles you sell to. It uses only the company's own public pages, no social networks or private data sources. Built for sales and partnership teams doing account research. Check local outreach and privacy rules before contacting anyone.

How it works

1. Daily schedule / manual run reads every setting from Config. A weekly schedule uses the same Config to send a report instead of running the actor.
2. Starts the Apify actor asynchronously, then waits and polls the run; FAILED, ABORTED, TIMED-OUT or too many polls stop with an error.
3. Downloads the dataset, validates rows and dedupes within the run and across runs (workflow static data, dedupeMemoryDays).
4. A transparent rule score runs first, then an LLM chain with a structured output parser reads each record against your plain-English aiCriteria and returns a fit score, verdict, summary, outreach angle and red flags. Calls are batched with a delay for rate limits, retried, and fall back to the rule score if the model fails.
5. Upserts every row to Google Sheets. Hot rows go to Slack as one approve / dismiss message (send-and-wait, 24 h limit) and the decision is written back to the sheet; warm rows go to an HTML email digest; cold rows stay in the sheet.
6. Weekly report: reads the sheet, summarises the last 7 days (tiers, approvals, top 10) and emails it.
7. A separate Error Trigger branch posts any failure to Slack.

Setup (about 15 minutes)

1. Create an HTTP Header Auth credential: name Authorization, value Bearer <APIFY_API_TOKEN> (Apify Console > Settings > API & Integrations). Select it on the 3 Apify HTTP nodes.
2. Create a Google Sheet with a tab named in sheetTab and a header row matching the sheet columns (see Upsert to Google Sheets, plus status and reviewedAt). Paste its ID into googleSheetId.
3. Connect OpenAI (or swap the chat model sub-node for Anthropic, Gemini, Ollama...), Slack and Gmail; set slackChannelId and digestEmail in Config (also the channel on Slack: error alert).
4. In Config set actorInput.domains, minSeniority (manager, director, vp_partner, c_level) and targetTitles (fragments of the titles you sell to).
5. Write your ideal-lead description in aiCriteria; set aiWeight (0 = rules only, 1 = AI only).
6. Run once manually, check the sheet, then activate.

Customize

• Edit weights in Score decision makers (seniority up to 35, title match 25, published email 20, confidence 15, source page 5).
• Rows are keyed by domain and name, so the same person is not alerted twice.
• Swap Gmail/Slack for Teams, Discord, HubSpot, Airtable, etc. Each delivery node only reads $json.

Disclosure: I maintain these Apify actors (account transparent_meteorite). The actor is a paid pay-per-event Apify tool; check its Store page for current pricing before scheduling.