enrich-founders

name	enrich-founders
description	Enrich founder profiles for each sourced YC company. Uses Exa people search to fill missing LinkedIn URLs and professional bios. Apify bulk-email-finder for any missing founder emails. Clearly labels all inferred data. Triggers on: "enrich founders", "find founder details", "get founder info", "step 2", "next step", "continue to enrich founders", "enrich people".

Enrich Founders

Pipeline: source-ycombinator → enrich-founders → scrape-website → find-latest-news → find-latest-fundraise → export-csv

You are step 2 of 5. Your job is to enrich founder profiles for every company in yc_companies.json — filling missing LinkedIn URLs, emails, and bios.

Tools

• Exa MCP (people_search_exa) — primary: find missing LinkedIn URLs and professional bios
• Apify MCP (icypeas_official/bulk-email-finder) — find missing founder emails by name + company domain
• WebSearch / WebFetch — fallback for checking company team pages

Input

Read data/raw/yc_companies.json. If the file does not exist, stop and ask the VC to run source-ycombinator first.

Extract all founders across all companies. The YC scraper already provides:

• name, title, bio (from YC profile)
• emails.email, emails.status (from YC scraper — already high quality)
• linkedin, x (from YC profile — may be null)

Step 1: Identify gaps

For each founder, flag which fields are missing:

• linkedin is null → needs Exa lookup
• email is null or email_status is risky → needs email finder
• bio is null or very short (< 50 chars) → needs Exa bio enrichment

Skip enrichment for founders who already have all fields populated.

Step 2: Fill missing LinkedIn URLs via Exa

For founders missing a linkedin URL:

Use Exa MCP people_search_exa:

"[founder name]" "[company name]" founder OR CEO OR CTO

Extract the LinkedIn URL from the result. If multiple candidates, pick the one matching the company name.

If not found, leave linkedin: null — do not fabricate a URL.

Set linkedin_source: "exa" on any newly found LinkedIn URL.

Step 3: Fill missing emails via Apify

For founders where email is null or risky, build a CSV for batch email lookup:

Extract the domain from the company's website field (e.g. starsling.dev from https://www.starsling.dev/). Strip www. and protocol.

Format the CSV:

firstName,lastName,domain
Sarah,Smith,starsling.dev
James,Lee,sequoia.com

Run Apify actor icypeas_official/bulk-email-finder with the prospect CSV.

The actor returns:

• email — found email address
• confidence — confidence score (0.0–1.0)
• status — found, not_found, or risky

Map results back to founders by firstName + lastName + domain.

Assign email_tier:

Actor status	confidence	email_tier
found	≥ 0.8	confirmed
found	< 0.8	inferred
not_found or risky	—	not_found

Set email_source: "icypeas" for any found email from this step.

Note: Founders from the YC scraper with email_status: "verified" already have email_tier: "confirmed" — do not re-run the email finder for those.

Step 4: Enrich missing bios via Exa

For founders with a short or missing bio:

Use Exa MCP people_search_exa:

"[founder name]" "[company name]"

Extract a 2–3 sentence professional bio from the result. Trim to relevant highlights (prior companies, roles, notable exits).

Set bio_source: "exa" on any newly added bio content.

Step 5: Merge enriched data

For each founder, produce a merged record by:

1. Starting with the original YC data
2. Filling linkedin if previously null and found via Exa
3. Filling/upgrading email and email_tier if the bulk finder found a better result
4. Filling bio if previously short and Exa returned content

Do not overwrite confirmed YC-sourced emails with lower-confidence Exa results.

Output

Update each company's founders array in place, then write the enriched dataset to data/normalized/enriched_founders.json.

Schema: schemas/founder_profile.schema.json

Each founder record must include:

• company_id, company_name (from parent company)
• founder_id, name, title, bio, bio_source
• email, email_status, email_tier, email_source
• linkedin, linkedin_source
• x

Review checkpoint

After writing data/normalized/enriched_founders.json, present a summary:

Enriched [N] founders across [M] companies:

Contact quality:
  ✓ Confirmed email (YC verified or high confidence): [N]
  ~ Inferred email (lower confidence): [N]
  ✗ No email found: [N]

  LinkedIn found: [N] / [total]
  Bio enriched via Exa: [N] founders

Sample:
| Company | Founder | Email | Tier | LinkedIn |
|---------|---------|-------|------|---------|
| ... | ... | ... | confirmed | yes/no |
...

Does this look right? You can:
  - Confirm to proceed to step 3 (scrape websites)
  - Correct a founder's email: "update email for [name] to [email]"
  - Remove a founder: "remove [name] from [company]"

Do not proceed to scrape-website until the VC confirms.