Query a specific source (founders, investors, companies, funding-rounds, valuations) with structured filter syntax.
Filter syntax (filter param):
filter=key[op]:valuefilter=and(key1[op]:val1,key2[op]:val2)filter=or(key1[op]:val1,key2[op]:val2)filter=and(tag_id[eq]:42,or(location[eq]:81,location[eq]:74))Available operators: eq, neq, gt, gte, lt, lte, in_any, nin_any, in_all, nin_all
in_all / nin_all are only exposed on repeated related-record filters.
Filter types:
launch_year[gte]:2020, total_funding_usd[gt]:1000000, is_unicorn[eq]:truelocation[eq]:81, location[in_any]:1234|5678tag_id[eq]:42, tag_id[nin_any]:99region[eq]:123Examples:
?metric=count&group_by=hq_country&filter=tag_id[eq]:42?metric=count&group_by=launch_year&filter=and(is_funded[eq]:true,launch_year[gte]:2015)?metric=sum:amount_usd&group_by=year,hq_countryAuth0 JWT access token
The source to aggregate (founders, investors, companies, funding-rounds, valuations)
founders, investors, companies, funding-rounds, valuations, entities, fundings "founders"
Metric to compute: count, count_distinct:field, sum:field, avg:field, median:field, p25:field, p75:field
1"count"
Dimension(s) to group by. Location dims: hq_country, hq_city, hq_state, hq_continent, macro_region, region. Relationship fields: university.name, employer.city. Multi-dim: year,hq_country
1^[a-z][a-z0-9_.]*(?:,[a-z][a-z0-9_.]*)*$"hq_country"
Filter expression using structured syntax: and(key[op]:value,...), or(...). Example: and(tag_id[eq]:42,location[eq]:81)
"and(tag_id[eq]:42,launch_year[gte]:2020)"
Sort by metric key or 'dimension'. Prefix with - for descending
^-?[a-z][a-z0-9_]*$"-count"
Number of results to return (1-500, default 25)
"25"