Lima data api

Lima Data Search & Enrich through ColdIQ

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.

1. Try name + company domain. → POST /v1/limadata/find/work-email · 1 cr · limadata.find.work_email

   { "full_name": "William Gates", "company_domain": "microsoft.com" }
   

2. 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" }
   

3. 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

1. Resolve exact filter values (titles, industries) so you don't waste a 25-credit page. → POST /v1/limadata/references/autocomplete · free · limadata.references.autocomplete
2. 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).

1. 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" }
   

2. 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).