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Fiber AI Profiles Text-to-Search-Params
contactsemailphoneenrichmentdata
Fiber AI Profiles Text-to-Search-Params is a paid API for AI agents from Fiber AI API at mpp.orthogonal.com, paid per call via MPP, $0.04/call, status unknown (last checked 2026-10-11).
Converts free-form natural language describing a person profile (e.g. 'Software engineers in US with 5+ years of experience') into structured search parameters for querying people/profiles.
Price / call$0.04
Success—
StatusUnknown
How this service works
Takes free-form text (e.g., 'Software engineers in US with 5+ years of experience') and converts it into a structured set of filters for profile search. This endpoint helps transform natural language queries into standardized search parameters such as job titles, skills, seniority, locations, past experiences, education, languages, and more.
Output
A structured object containing parsed search parameters derived from the natural language input, suitable for use in a downstream profile/people search query — including fields like job title, location, years of experience, and company attributes.
Example use cases
Find qualified candidates for tech roles
“Turn this into search filters for me: 'Product managers based in San Francisco who have worked at late-stage startups and know React'”
Build sales prospecting list quickly
“I need to search for people matching this description: 'Enterprise sales directors in the US with experience selling to Fortune 500 companies and at least 10 years in SaaS'. Can you convert that into structured search parameters?”
Identify potential board advisors
“Convert this into profile search criteria: 'Former CTOs or VP Engineers who founded companies, speak Spanish, and have experience in fintech or healthcare'”
Technical details
Endpoint
POSThttps://mpp.orthogonal.com/fiber/v1/text-to-search-params/profiles?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have a natural language description of a target person/profile and need to convert it into structured search parameters before calling a profile search API. Ideal for LLM-driven workflows where the user expresses their ideal contact or candidate in plain English rather than filling out a structured form. Prefer this over directly calling a search endpoint when the input is unstructured text.
Side effects
- Ambiguous or too-vague natural language input results in incomplete or low-confidence parameters
- Input text describing non-person entities (e.g. companies) may return malformed parameters
- Very niche or highly specific criteria may not map cleanly to known filter fields
- Missing required body payload returns 400 Bad Request
- Authentication failure returns 401 Unauthorized
Input
{
"query": "Software engineers in the United States with 5+ years of experience"
}Output
{
"output": {
"searchParams": {
"jobStatus": {
"status": "currently-employed"
},
"jobTitleV3": {
"anyOf": [
{
"term": "Software Engineer",
"type": "plain"
}
]
},
"yearsOfExperience": {
"lowerBound": 5
},
"country3LetterCode": {
"anyOf": [
"USA"
]
}
}
},
"chargeInfo": {
"method": "charged-now",
"creditsCharged": 2
}
}Tags
contactsemailphoneenrichmentdata
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