Find people and companies, enrich them with emails/phones/firmographics, and prospect at
scale — all through the ColdIQ marketplace API with one key and unified credits. Lima Data
/v1/limadata/* endpoints cover find/enrich/prospect/search; /v1/ai-ark/* covers large-database
search.
ColdIQ Marketplace Endpoints
| Task | Method | Path | Credits | Endpoint ID | Notes |
|---|---|---|---|---|---|
| Find work email (name + domain) | POST | /v1/limadata/find/work-email |
1 | limadata.find.work_email |
Free if not found |
| Find work email (LinkedIn URL) | POST | /v1/limadata/find/work-email-linkedin |
3 | limadata.find.work_email_linkedin |
Fallback when domain missing |
| Find personal email | POST | /v1/limadata/find/personal-email |
5 | limadata.find.personal_email |
Free if not found |
| Find phone | POST | /v1/limadata/find/phone |
10 | limadata.find.phone |
Free if not found |
| Enrich person | POST | /v1/limadata/enrich/person |
1–5 | limadata.enrich.person |
LinkedIn=1, name+company=2, personal email=5 |
| Enrich company | POST | /v1/limadata/enrich/company |
1 | limadata.enrich.company |
Firmographics, funding, tech, traffic |
| Prospect people (filter) | POST | /v1/limadata/prospect/people/filter |
25 | limadata.prospect.people.filter |
Sales-Nav-style, 25/page |
| Prospect people (SN URL) | POST | /v1/limadata/prospect/people/search-url |
25 | limadata.prospect.people.search_url |
Paste a Sales Navigator URL |
| Prospect employees of a company | POST | /v1/limadata/prospect/employees |
25 | limadata.prospect.employees |
Title/location/seniority filters |
| Prospect companies (filter) | POST | /v1/limadata/prospect/companies/filter |
25 | limadata.prospect.companies.filter |
Firmographic filters |
| Batch prospect people (async) | POST | /v1/limadata/batch/prospect-people |
1/entity | limadata.batch.prospect_people |
Cheaper at scale; poll results |
| Batch people profiles (async) | POST | /v1/limadata/batch/people |
1/URL | limadata.batch.people |
LinkedIn URLs → profiles |
| Get batch results | POST | /v1/limadata/batch/results |
free | limadata.batch.results |
Poll every ~60s |
| Autocomplete filter values | POST | /v1/limadata/references/autocomplete |
free | limadata.references.autocomplete |
Resolve titles/industries/etc. |
| Web search | POST | /v1/limadata/search/web |
0.1 | limadata.search.web |
Google web search |
| Large-scale people search | POST | /v1/ai-ark/people |
per result | ai_ark.people.search |
500M profiles; use for big lists |
| Large-scale company search | POST | /v1/ai-ark/companies |
per result | ai_ark.companies.search |
70M companies |
Quick Reference
- Base URL:
https://api.coldiq.com - Auth: API key header (see resources/auth.md — header unverified)
- Credits: every call settles against your ColdIQ balance; check via
/dashboard/credits - Not charged when a find endpoint returns nothing (
free_if_not_found)
Find Emails (Waterfall)
Cheapest-first. Stop at the first hit.
- Try name + company domain.
→ POST
/v1/limadata/find/work-email· 1 cr ·limadata.find.work_email{ "full_name": "William Gates", "company_domain": "microsoft.com" } - If the domain is missing or step 1 is empty, fall back to the LinkedIn URL.
→ POST
/v1/limadata/find/work-email-linkedin· 3 cr ·limadata.find.work_email_linkedin{ "linkedin_url": "https://linkedin.com/in/williamgates" } - Personal email as a last resort.
→ POST
/v1/limadata/find/personal-email· 5 cr ·limadata.find.personal_email
Find rate is typically 60–70% for work emails. Always verify before sending (see contact-enrichment).
Prospect People at Target Companies
- Resolve exact filter values (titles, industries) so you don't waste a 25-credit page.
→ POST
/v1/limadata/references/autocomplete· free ·limadata.references.autocomplete - Run the live prospect with company + title + location filters (25 results/page).
→ POST
/v1/limadata/prospect/people/filter· 25 cr ·limadata.prospect.people.filter{ "filters": [ {"filter_type": "company", "operator": "in", "values": ["https://linkedin.com/company/microsoft"]}, {"filter_type": "current_title", "operator": "in", "values": ["Chief Marketing Officer"]}, {"filter_type": "location", "operator": "in", "values": ["San Francisco Bay Area"]} ], "page": 1 }
Common filter types: company, current_title, seniority (Owner / Partner, CXO,
Vice President, Director, Senior), location, industry, company_headcount
(1-10 … 10,001+), function, recently_changed_jobs.
Already have a Sales Navigator search URL? Skip the filter-building:
→ POST /v1/limadata/prospect/people/search-url · 25 cr · limadata.prospect.people.search_url
Want everyone at one company? Use the employee finder:
→ POST /v1/limadata/prospect/employees · 25 cr · limadata.prospect.employees
Batch Prospect (Large Lists)
For lists above a few hundred, batch is 25× cheaper than live prospecting (1 cr/entity vs 25/page).
- Submit the batch (entity count a multiple of 25).
→ POST
/v1/limadata/batch/prospect-people· 1/entity ·limadata.batch.prospect_people{ "name": "CMOs at target companies", "filters": [ ... ], "entity_count": 2500, "notification_url": "https://your-webhook.com/batch-complete" } - Poll until
completed(pull pages as they finish — don't wait for the whole job). → POST/v1/limadata/batch/results· free ·limadata.batch.results
Status flow: pending → processing → completed | failed. See
resources/async-job-pattern.md for the generic poll loop.
To turn a list of LinkedIn profile URLs into full profiles, use
→ POST /v1/limadata/batch/people · 1/URL · limadata.batch.people
Enrich
- Person — pick one input (LinkedIn=1 cr, work email=1, name+company=2, personal email=5):
→ POST
/v1/limadata/enrich/person· 1–5 cr ·limadata.enrich.person - Company — by domain or LinkedIn URL; returns firmographics, funding, tech stack, traffic:
→ POST
/v1/limadata/enrich/company· 1 cr ·limadata.enrich.company
When to use Lima Data vs ai-ark vs Apollo
| Need | Best | Why |
|---|---|---|
| People at specific companies | limadata.prospect.people.filter |
Sales-Nav-style filters, batch support |
| Very large people lists | ai_ark.people.search |
500M profiles, per-result pricing |
| Apollo-specific filter semantics | apollo-search skill | Apollo's 65+ filters / intent topics |
| Enrich known contact → email | limadata.find.work_email* |
1 cr name+domain, 3 cr LinkedIn |
| Company firmographics in one call | limadata.enrich.company |
Funding, revenue, tech stack together |
| Web / AI research | limadata.search.web, limadata.research.ai_search |
0.1–0.3 cr |
Tips
- Title formatting: "VP SEO" not "VP, SEO" (no comma between prefix and role).
- Resolve filter values first with autocomplete — a misspelled title silently returns 0 and still costs a prospect page.
- Dedup before enriching (see list-dedup) so you never pay twice for the same person.
- Cache: people data 30 days (job changes), company data 90 days (firmographics move slowly).