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Ocean.io Company Search API
x402
Ocean.io Company Search API is a paid API for AI agents from x402.orthogonal.com, paid per call via x402, $1/call, status unknown (last checked 2026-09-16).
Search for enriched company profiles using filters like industry, size, location, technologies, revenue, headcount growth, and lookalike domains, with pagination support.
Price / call$1
Success—
StatusUnknown
How this service works
Search for companies using filters (industry, size, location, technologies, revenue, headcount growth, etc.) and/or lookalike domains. Returns enriched company profiles. Use the size parameter to control max results (1-10,000), defaults to 50. Use searchAfter from the previous response to paginate.
Output
Returns an array of enriched company profile objects, each containing requested fields such as domain, name, employee count, industry categories, technologies, revenue, locations, web traffic, funding round, headcount growth, emails, and phones. Also includes a searchAfter pagination cursor for retrieving subsequent pages of results.
Example use cases
Competitor lookalike prospecting
“Find me 200 companies that look similar to salesforce.com — same industry and size — operating in North America, and return their domain, company name, employee count, and technologies they use.”
Targeted outbound lead list
“I need a list of 500 fintech companies in Europe with 100 to 1000 employees that have a Director or VP of Finance on staff — give me their domain, location, and revenue estimates.”
Tech stack market analysis
“Search for up to 1000 ecommerce companies globally that use Shopify and have more than $5M in revenue, and return their name, domain, country, headcount, and web traffic data.”
Technical details
Endpoint
POSThttps://x402.orthogonal.com/ocean-io/v3/search/companiesWhen to prefer
Use this endpoint when you need to discover or build lists of companies matching specific firmographic, technographic, or people-based criteria at scale. Prefer it over general web search for structured B2B prospecting, market segmentation, competitive intelligence, or lookalike modeling. It's especially valuable when you need paginated, enriched company profiles with fields like headcount growth, technologies, and revenue — not just a name and URL.
Side effects
- Invalid filter combination returns empty results or 400 error
- Exceeding size limit of 10,000 returns validation error
- Invalid searchAfter cursor causes pagination failure
- Missing or malformed peopleFilters fields return 400
- Unsupported field name in fields array causes error
- Payment failure ($1 USDC) prevents request from being processed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| size | integer | Max results to return (1-10,000). Default: 50. |
| fields | array | string[] - Fields to return in Company objects (reduces bandwidth). Options: "domain", "countries", "primaryCountry", "companySize", "industryCategories", "industries", "linkedinIndustry", "ecommerce", "keywords", "employeeCountOcean", "employeeCountLinkedin", "revenue", "yearFounded", "description", "emails", "phones", "logo", "technologies", "technologyCategories", "mobileApps", "webTraffic", "medias", "name", "legalName", "locations", "departmentSizes", "rootUrl", "faxes", "impressum", "fundingRound", "redirectedFrom", "updatedAt", "headcountGrowth", "headcountGrowthPerDepartment". Nested fields also supported (e.g. "phones.number", "webTraffic.visits", "medias.linkedin", "locations.country"). |
| searchAfter | string | Pagination cursor returned by the previous response to get the next page of results. |
| peopleFilters | object | People filters to find companies with matching employees: lookalikeLinkedinHandles: string[], countries: string[] (ISO 3166 alpha-2), excludeCountries: string[], regions: string[], states: object[] ({country: string, abbreviation: string}), excludeStates: object[], cities: object[] ({country: string, city: string}), names: string[], seniorities: string[] (enum: "Owner", "Founder", "Board Member", "C-Level", "Partner", "VP", "Head", "Director", "Manager", "Other"), departments: string[] (enum: "Accounting and Finance", "Board", "Business Support", "Customer Relations", "Design", "Editorial Personnel", "Engineering", "Founder/Owner", "Healthcare", "HR", "Legal", "Management", "Manufacturing", "Marketing and Advertising", "Operations", "PR and Communications", "Procurement", "Product", "Quality Control", "R&D", "Sales", "Security", "Supply Chain", "Other"), jobTitleKeywords: object {anyOf: string[], allOf: string[], noneOf: string[]}, skills: object {anyOf: string[], allOf: string[], noneOf: string[]}, allJobDescriptions: object {anyOf: string[], allOf: string[], noneOf: string[]}, currentJobDescription: object {anyOf: string[], allOf: string[], noneOf: string[]}, profileDescription: object {anyOf: string[], allOf: string[], noneOf: string[]}, includePeopleIds: string[], includeLinkedinHandles: string[], excludePeopleIds: string[], excludeLinkedinHandles: string[], fieldsExist: string[], fieldsNotExist: string[], changedPositionAfter: string (YYYY-MM-DD), changedPositionBefore: string (YYYY-MM-DD), updatedWithinMonths: integer |
| companiesFilters | object | Company filters object with these fields: lookalikeDomains: string[] (domains to find similar companies), includeDomains: string[] (only return these domains), excludeDomains: string[] (exclude these domains), companySizes: string[] (enum: "0-1", "2-10", "11-50", "51-200", "201-500", "501-1000", "1001-5000", "5001-10000", "10001-50000", "50001-100000", "100001-500000", "500000+"), revenues: string[] (enum: "0-1M", "1-10M", "10-50M", "50-100M", "100-500M", "500-1000M", ">1000M"), primaryLocations: object {includeCountries: string[] (ISO 3166 alpha-2 codes), excludeCountries: string[], includeRegions: object[] ({country: string, region: string}), excludeRegions: object[], includeCities: object[] ({country: string, city: string}), excludeCities: object[], geolocation: object {latitude: number, longitude: number, radius: integer (meters)}}, otherLocations: object (same structure as primaryLocations), industries: object {industries: string[] (values from /v2/data-fields), mode: string ("anyOf"|"allOf")}, excludeIndustries: string[], industryCategories: object {industryCategories: string[], mode: string}, excludeIndustryCategories: string[], linkedinIndustries: string[], excludeLinkedinIndustries: string[], technologies: object {apps: object {anyOf: string[], allOf: string[], noneOf: string[]}, categories: object {anyOf: string[], allOf: string[], noneOf: string[]}}, keywords: object {anyOf: string[], allOf: string[], noneOf: string[]}, yearFounded: object {from: integer, to: integer}, employeeCountOcean: object {from: integer, to: integer}, employeeCountLinkedin: object {from: integer, to: integer}, ecommerce: boolean, headcountGrowth: object {asPercentage: boolean (required), growthRange: object {from: number, to: number} (required), months: string (enum: "Three months", "Six months", "Twelve months") (required)}, departmentHeadcountGrowth: object {anyOf: object[], allOf: object[]}, webTraffic: object {visits: object {from: integer, to: integer}, views: object {from: integer, to: integer}}, socialMedias: object {medias: object {anyOf: string[], allOf: string[], noneOf: string[]}, minCount: integer}, mobileApps: object {from: integer, to: integer}, fundingRound: object {types: string[] (enum: "Seed", "Series A", "Angel", "Series B", "Pre-Seed", "Grant", "Series C", "Convertible Note", "Debt Financing", "Series D", "Corporate Round", "Private Equity", etc.), raised: object {from: integer, to: integer}, date: object {from: string (YYYY-MM-DD), to: string}}, locationsCount: object {from: integer, to: integer}, countriesCount: object {from: integer, to: integer}, departmentSizes: object[] ({department: string, from: integer, to: integer}), updatedWithinMonths: integer, minRelevance: string (A is most relevant), maxRelevance: string, companyMatchingMode: string ("precise"|"broad") |
Tags
x402
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