> ## Documentation Index > Fetch the complete documentation index at: https://docs.datamagnet.co/llms.txt > Use this file to discover all available pages before exploring further. # People Search DB > Search Datamagnet's own database of previously enriched LinkedIn profiles by keyword, location, company, job title, and more — with include/exclude support for company LinkedIn URLs. # People Search DB **Cost:** `10` credits/search. Search Datamagnet's internal database of already-enriched LinkedIn profiles. Unlike [ICP People Search](/api-reference/endpoints/icp-people-search), which queries LinkedIn live, this endpoint searches previously collected profile records — so it returns instantly and doesn't consume LinkedIn scraping capacity. Each page returns up to `50` results. For companies rather than people, see [Company Search DB](/api-reference/endpoints/company-db-search). ## People search DB endpoint Most filter fields accept multiple values. Values within the same field are OR'd together (e.g. `["San Francisco", "New York"]` matches either city); different fields are AND'd together. Booleans such as `open_to_work` take a single value. Filters that use a fixed vocabulary — `seniority`, `ownership`, `functions`, `degree_levels`, `fields_of_study`, `employment_types` — reject a value they don't recognise with a `422` that lists what is accepted. They never quietly return zero results for a word we couldn't read. ### Free text Keyword search across name and headline. Also accepted as `q`; if both are sent, `keyword` wins. Words shorter than three characters are dropped, and the remaining words are OR'd — `"operations manufacturing quality"` matches a profile containing **any** of those words, not all three. Adding words broadens the search; use the structured filters below to narrow it. Example: `software engineer` ### Location Filter by country, matched exactly (case-insensitive) against the stored country name. For a substring match, include a `%` wildcard in the value — e.g. `["United %"]`. Example: `["United States", "Canada"]` Filter by full location string. Partial match. Example: `["Greater New York City Area"]` Filter by city. Partial match, against both the parsed city and the full location string. Example: `["San Francisco", "Austin"]` Filter by state/region. Partial match, against both the parsed state and the full location string. Example: `["California"]` ### Current company A "current" position is one the profile still holds — the company filters, `employment_types` and `employer_industries` all read it the same way. Filter by current company name. Partial match. Example: `["Stripe", "Plaid"]` Filter by current company using its LinkedIn URL. Accepts a full URL, universal name, or numeric LinkedIn company ID. Example: `["https://www.linkedin.com/company/stripe/"]` Exclude profiles whose **current** company matches any of these LinkedIn URLs. Accepts the same formats as `company_linkedin_urls` (full URL, universal name, or numeric ID). Useful for filtering out a competitor or your own company from results. Example: `["https://www.linkedin.com/company/competitor-co/"]` Filter by the current employer's industry, matched exactly (case-insensitive). Resolved from the employer's company page where the profile itself doesn't carry an industry, which answers for roughly three quarters of people. Example: `["Financial Services", "Software Development"]` ### Past company Filter by a company the person has **left** (the position has an end date). Partial match. Example: `["Google"]` Same as `past_companies`, by LinkedIn URL, universal name, or numeric ID. Example: `["https://www.linkedin.com/company/google/"]` ### Role Filter by job title. Partial match, against **any** position on the profile — current or past. Use `seniority` or `functions` when you want the role the person holds now. Example: `["CTO", "VP of Engineering"]` Filter by the seniority of the current role, derived from the job title. Accepts our own labels — `Intern`, `Entry`, `Individual`, `Senior`, `Lead`, `Manager`, `Director`, `VP`, `C-suite` — or the LinkedIn Sales Navigator words the [ICP People Search](/api-reference/endpoints/icp-people-search) endpoint uses (`cxo`, `c-level`, `vice president`, `vp`, `director`, `manager`, `experienced manager`, `entry level manager`, `strategic`, `senior`, `entry level`, `in training`, `intern`). Spelling is forgiving about case, spaces, hyphens and underscores. `owner`, `founder` and `partner` are accepted here too and resolve to the ownership axis below, so `["VP", "founder"]` returns both groups. Example: `["VP", "C-suite"]` Filter by ownership of the business, which is a separate axis from seniority — an owner is not a rung above a VP. Accepted values: `owner_founder` (also spelled `owner`, `founder`, `co-founder`, `self employed`) and `partner`. Example: `["owner_founder"]` Filter by department/function of the current role, from Datamagnet's 40-function taxonomy. Accepts the name or its numeric id. `Software Engineering`, `Data & Analytics`, `IT & Systems`, `Information Security`, `Infrastructure & DevOps`, `Quality Assurance`, `Product Management`, `Design & UX`, `Sales`, `Business Development`, `Marketing`, `Revenue Operations`, `Customer Success`, `Customer Support`, `Finance`, `Accounting`, `Legal & Compliance`, `Human Resources`, `Recruiting & Talent`, `Administrative`, `Business Operations`, `Supply Chain & Logistics`, `Manufacturing & Production`, `Procurement`, `Engineering (non-software)`, `Construction & Skilled Trades`, `Facilities & Real Estate`, `Transportation & Drivers`, `Consulting`, `Healthcare & Clinical`, `Education & Teaching`, `Research & Science`, `Media & Communications`, `Arts & Entertainment`, `Hospitality & Food Service`, `Retail`, `Public Sector`, `Protective Services`, `Social & Community Services`, `Agriculture & Environment`. Titles that name no department (a bare "Founder", for example) hold no function and are excluded rather than guessed at. Example: `["Sales", "Marketing"]` Filter by the employment type of the **current** role. Accepted values: `full_time`, `part_time`, `contract`, `freelance`, `self_employed`, `internship`, `apprenticeship`, `seasonal`. Each value covers the spellings LinkedIn uses for it — `contract` also matches `Temporary`, `internship` also matches `Co-op`, and so on. A profile whose employment type was never recorded matches none of them. Example: `["contract", "freelance"]` ### Tenure These read the start date of the current role. That date is as fresh as the profile's last refresh, so a very recent job change may not be reflected yet — the filter can miss a change, never invent one. Started their current role within the last N days. Example: `90` At least N months in the current role. Example: `12` At most N months in the current role. Example: `6` ### Education The education filters must all be satisfied by the **same** degree — `degree_levels: ["bachelor"]` with `fields_of_study: ["Computer and Information Sciences"]` means one bachelor's in computing, not a bachelor's in history plus a doctorate in computing. Filter by school name. Partial match. Example: `["Stanford"]` Accepted values: `secondary`, `associate`, `bachelor`, `master`, `doctorate`. Common spellings resolve to these — `bachelors`, `masters`, `phd`, `high school`. Example: `["bachelor", "master"]` Filter by field of study, grouped into 47 CIP families. Accepts the family name or its numeric id — e.g. `Computer and Information Sciences`, `Engineering`, `Business, Management, Marketing and Related Support Services`, `Health Professions and Related Programs`, `Social Sciences`. A `422` lists all of them. Example: `["Computer and Information Sciences"]` Degree ended in or after this year. Example: `2015` Degree ended in or before this year. Example: `2020` ### Credentials and skills Filter by listed skill, matched exactly (case-insensitive) against the skill name. Example: `["Kubernetes", "Terraform"]` Filter by certification name. Partial match. Must hold on the same certification as `certification_issuers`. Example: `["AWS Certified Solutions Architect"]` Filter by issuing organization. Partial match. Example: `["Amazon Web Services"]` Filter by a language listed on the profile, matched exactly (case-insensitive) as LinkedIn spells it. Example: `["German", "Spanish"]` ### Profile attributes Filter by the LinkedIn open-to-work badge. This filter is tri-state rather than a plain on/off switch. `true` returns profiles where the badge was seen. `false` returns profiles that were checked by a provider that reads the badge and did not have it. Profiles nobody has checked yet hold no badge information at all and are excluded from both sides, so `false` is **not** the complement of `true`, and leaving the field out is not the same as sending `false`. Example: `true` Filter by LinkedIn Premium. Example: `true` Filter by LinkedIn creator mode. Example: `true` Minimum follower count. Example: `1000` ### Contactability `true` returns only profiles Datamagnet currently holds an email address for; `false` returns only those it holds none for. Like `open_to_work`, this describes our records, not the person — `false` is not a claim that they have no email. Example: `true` As `has_email`, for phone numbers. Example: `true` ### Response shape and paging Whether to include the full `raw_data` payload on each result. Send `false` to omit it — the response is much smaller and the search is faster, and every other field is unaffected. Maximum number of results to return per page, from `1` to `50`. A value outside that range is rejected rather than quietly reduced — page through larger result sets with `offset`. Number of results to skip, for pagination. ### Unrecognised fields A field name this endpoint doesn't know is not applied. The search still runs, and the response carries an `ignored_filters` array naming what was dropped — so a mistyped `job_title` (for `job_titles`) shows up as a named mistake instead of a page of results that looks filtered but isn't. If **every** filter in the request was unrecognised, the search is refused with a `422` and no credits are charged, rather than run as an unfiltered scan of the whole database. *** ## Response ```json Request theme={null} { "keyword": "software engineer", "cities": ["San Francisco"], "company_linkedin_urls": ["https://www.linkedin.com/company/stripe/"], "exclude_company_linkedin_urls": ["https://www.linkedin.com/company/competitor-co/"], "job_titles": ["Backend Engineer"], "seniority": ["Senior", "Lead"], "functions": ["Software Engineering"], "degree_levels": ["bachelor"], "min_months_in_role": 12, "has_email": true, "open_to_work": true, "raw_data": false, "limit": 50, "offset": 0 } ``` ```json Response theme={null} { "message": [ { "id": 10432, "entity_urn": "ACoAAC8Np1kB17Ro_b3eo8YZWUZFudbt9lrg1Tw", "username": "jane-doe-1234", "full_name": "Jane Doe", "display_name": "Jane Doe", "profile_headline": "Backend Engineer at Stripe", "description": "Building payments infrastructure.", "profile_link": "https://linkedin.com/in/jane-doe-1234", "location": "San Francisco, California, United States", "location_city": "San Francisco", "location_state": "California", "country": "United States", "followers": 1240, "connections": 500, "is_premium": true, "is_creator": false, "is_influencer": false, "is_job_seeker": false, "is_openlink": false, "is_retired": false, "open_to_work": true, "avatar_url": "https://media.licdn.com/dms/image/...", "profile_picture": "https://media.licdn.com/dms/image/...", "email": null, "linkedin_url": "https://linkedin.com/in/jane-doe-1234", "current_job_title": "Backend Engineer", "current_company": "Stripe", "current_job_location": "San Francisco, CA", "current_employment_type": "Full-time" } ], "credit_used": 10, "total": 1 } ``` ## The response model ### Properties List of matching profiles. Internal Datamagnet profile ID. LinkedIn entity URN. LinkedIn username/vanity URL. Full name of the person. Display name as shown on LinkedIn. LinkedIn profile headline. Profile description/about section. LinkedIn profile URL. Full location string. City of the profile's location. State/region of the profile's location. Country of the profile's location. Number of LinkedIn followers. Number of LinkedIn connections. Whether the person has LinkedIn Premium. Whether the person is a LinkedIn creator. Whether the person is a LinkedIn influencer. Whether the person is marked as a job seeker. Whether the person uses OpenLink. Whether the person is marked as retired. Whether the person carries the LinkedIn open-to-work badge. `null` when no provider that reads the badge has checked this profile, which is true of most of the database — it is not the same as `false`. Profile picture URL. Profile picture URL (alternate source). Email address, when available. May be `null`. Computed LinkedIn profile URL, built from `username`. Job title of the profile's current position, when available. Name of the profile's current company, when available. Location of the profile's current position, when available. Employment type of the current position (e.g. `Full-time`), when available. The full stored payload this profile was built from. Included by default; send `raw_data: false` in the request to omit it. Number of credits used for this request. Example: `10` Number of results returned in this response. Present only when the request contained field names this endpoint doesn't recognise. Names them, so a typo shows up as a typo rather than as results that look filtered but aren't. The rest of the search ran normally. ## Errors | Status | Meaning | What to do | | ------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- | | `400` | The body was not a JSON object, or `limit` was outside `1`–`50`, or `offset` was negative. `message` names the problem. | Fix the request. | | `422` | Either every filter in the request was an unrecognised field name, or a fixed-vocabulary filter was given a value that doesn't exist — an unknown function, a degree level that isn't one of the five. `message` names what was rejected and lists what is accepted. | Correct the name or the value. | | `504` | The search ran too long to answer. | Narrow it and retry — fewer countries, a more specific job title. A broad `keyword` with no structured filter beside it is the usual cause. | Nothing is charged on any error.