Outricher / brighty-app / anatomy of a profile

One person — up to 148 fields.

Everything you saw in the Brighty reports — the team, hiring, audience portraits — is built from a single building block: the person profile. This page is about that building block itself. One profile isn't a row in a list; it's a career, company, education, skills, contacts, and code stitched into one entity. And there are hundreds of millions of such entities in the graph.

50 → 148
fields per person — from an instant sample to full enrichment
116
fields on average per profile in the real Brighty dataset
100M+
profiles in the database — graph depth for any company
5B+
positions in career history — who worked where and when

prepared 2026-06-28 · MEASURED on the real dataset · Outricher data

00Why the profile is the unit of leverage

Most "contact databases" hand you disconnected lists: names here, emails there, companies elsewhere. Our unit is the stitched profile: one person = their career + current company + education + skills + contacts + public code, linked into a single object and pinned to a precise geolocation. That's exactly why you can assemble a company's team, a talent map, or an audience portrait from it — something a list of rows simply can't deliver.

Stitched
career + company + code + contacts — in one entity, not five lists
Deep
116 fields per person on average: role, tenure, location, education, skills
Fresh
the database updates continuously — not a three-year-old dump
On demand
any profile can be pulled live at the moment of the deal

01Three layers of enrichment

A profile unfolds in three stages. Each one adds data, while cost and time grow in a controlled way. Even at the first stage — 50 fields, contacts, scoring — you have enough to analyze. Full enrichment takes a profile up to ~130–148 fields with a complete career history.

Layer 1 — sample · instant · $0 Layer 2 — enrichment · career history Layer 3 — final assembly · maximum data
Layer 1 — Sample
~50 FIELDS · INSTANT · $0

What's available instantly when you sample the graph — no external calls, no delays. Already includes name, role, company, location, contacts, and scoring. Enough to segment the market and start real outreach — for many vendors this level is the whole product; here it's the free starting point.

First · last name
full name, for personalization
Role · title
current position — the primary ICP field
Company
name, domain, industry
Company size
bucket 1 / 2–10 / 11–50 … works even when the exact number is hidden
Founded year
company age and maturity
Location · country
city and country code — person-level geotargeting
Tenure in role
start date — "newcomers" evaluate tools 3–5× more often
Skills
skills array for precise role matching
Email
the best from a waterfall of sources
Phone
direct number — rare but valuable channel
Social · GitHub · X
extra contact channels, engineering footprint
Lead score
composite score + a "why" breakdown
Layer 2 — Enrichment
~100 FIELDS · + CAREER HISTORY

Adds the full career and education history plus professional context. This is what turns a "contact" into a "portrait of a person": where they worked before, what they studied, what they can do, what they do publicly.

Career history
all positions: company, role, dates, location, description
Education
school, degree, field of study, years
Certifications
professional qualifications
Languages
languages and proficiency level
Recommendations
peer endorsements — social proof
Activity · content
posts, articles — engagement level
Similar profiles
lookalike detection of peers and competitors
Accomplishments
awards, patents, publications, projects
Layer 3 — Final assembly
~130–148 FIELDS · MAXIMUM

A final reconciliation of the profile against the depth of the database: we top up contacts via the waterfall, add freshness signals and company intelligence. This is often where a "bonus" email or channel turns up that exists nowhere else.

Contact delta
union of all known emails + "new" ones found in the database
Profile freshness
last-activity date — the key "reachability" signal
Career depth
number of positions, number of recommenders
Company intelligence
description, type (public/private), parent company, brand strength
Income estimate
salary range — budget qualification
Demographics
gender — for DEI analytics

02What this means in numbers

Not a model and not marketing — this is a slice of a real dataset from one of the Brighty audience samples (929 profiles). Here's what the "average person" from the graph looks like after processing.

Depth
116
fields per profile on average
from 88 to 141 · 148 unique across the pool
Reachability
100%
of profiles are ready for outreach on at least one channel — email, social, or the profile itself
Completeness
96%
of profiles are assembled from the database — layer 3 applied, names and fields cleaned
An honest frame (and it works in our favor). We don't promise a contact for literally every person — nobody who's honest can. What we prove is that the company is the right type and the person is the right role in the right geography, and then we find every channel that actually exists for them. So we sell match precision, not inflated promises. That's the difference between us and list generators.

03What a single profile looks like

One real, complete object — an actual profile from a recent API pull (a Fractional CTO in London), exactly as the pipeline emits it after all four layers. Scroll the card: 114 fields — identity, role, company, geo, contacts, career, education, skills, availability signals, scoring, and the separate api_* layer, each source kept as its own field.

profile.json114 fields · real API pull · scroll ↓
{
  "profile_id": 10153971,
  "full_name": "Alfonso Ferrandez",
  "first_name": "Alfonso",
  "last_name": "Ferrandez",
  "headline": "The Restless CTO🔹AI Evangelist🔹Co-founder Equiyd🔹Educator🔹Advisor🔹DD🔹Fractional CTO",
  "title": "Fractional CTO",
  "function": "consulting_strategy",
  "role_bucket": "c_level",
  "seniority_tier": "A",
  "years_experience": 25,
  "company_name": "Little Journey",
  "company_domain": "littlejourney.health",
  "company_industry": null,
  "company_employee_count": 38,
  "company_id": "68278107",
  "current_position_title": "Fractional CTO",
  "current_position_company": "Little Journey",
  "current_position_start_year": 2024,
  "current_positions": [
    {
      "title": "Fractional CTO",
      "company_name": "Little Journey",
      "company_domain": "littlejourney.health",
      "company_employee_count": 38,
      "company_industry": null,
      "start_date": null
    },
    {
      "title": "Senior Technology Advisor",
      "company_name": "PLD Space",
      "company_domain": "pldspace.com",
      "company_employee_count": 480,
      "company_industry": "Airlines/Aviation",
      "start_date": null
    },
    {
      "title": "Fractional CTO",
      "company_name": "Fruitful Insights",
      "company_domain": "fruitfulinsights.co.uk",
      "company_employee_count": 6,
      "company_industry": null,
      "start_date": null
    }
  ],
  "current_positions_count": 8,
  "location_name": "Greater London, England, United Kingdom",
  "location_country_code": "GB",
  "email": "alfonso.ferrandez@doctorlink.com",
  "all_emails": [
    "alfonso.ferrandez@gmail.com",
    "alfonso.ferrandez@doctorlink.com",
    "alfonso.ferrandez@manorf1team.com",
    "alfonso@fruitfulinsights.co.uk"
  ],
  "personal_emails": [
    "alfonso.ferrandez@gmail.com",
    "alfonso.ferrandez@doctorlink.com"
  ],
  "personal_phone_numbers": [
    "+447803927928"
  ],
  "github_url": "github.com/drfonz",
  "twitter_url": "https://x.com/drfonz",
  "facebook_url": "facebook.com/alfonso.ferrandez",
  "public_profile_url": "profiles.outricher.com/p/alfonsoferrandez",
  "profile_uid": 10153971,
  "industry_code": 80,
  "activity_at": "2026-03-05T13:26:40.347Z",
  "skills": [
    "Leadership",
    "Public Speaking",
    "Software Development",
    "Software Design",
    "Mobile Applications",
    "C#",
    ".NET",
    "Software Engineering",
    "ASP.NET MVC",
    "JavaScript",
    "SQL",
    "AJAX"
  ],
  "db_experiences": [
    {
      "title": "Software Architect",
      "company": "Pace Micro Technology plc",
      "company_id": 165375,
      "location": null,
      "start_year": 2006,
      "end_year": 2008,
      "is_current": false,
      "summary": "As Software Architect at Pace I designed and managed the implementation of a complete software stack to manage the next generation settop boxes, with advanced algorithms and the creation of a novel rules engine to maximise the quality of the video displayed to the consumer."
    },
    {
      "title": "Software Developer",
      "company": "Sony Computer Entertainment Europe",
      "company_id": 57993393,
      "location": null,
      "start_year": 2001,
      "end_year": 2001,
      "is_current": false,
      "summary": null
    },
    {
      "title": "Technology Adviser",
      "company": "Friend MTS",
      "company_id": 2054922,
      "location": null,
      "start_year": 2023,
      "end_year": null,
      "is_current": null,
      "summary": "Friend MTS is a leading global provider of advanced content security and anti-piracy services and solutions. From forensic watermarking, fingerprint-augmented content monitoring and legal enforcement to actionable business intelligence, they disrupt real-world piracy to protect revenue for content owners, broadcasters and OTT service providers and maximise their investment in live, linear and on-demand high-value content. I'm currently supporting the market-leading content security company in r"
    },
    {
      "title": "Professor - Artificial Intelligence Executive Master",
      "company": "Instituto de Inteligencia Artificial",
      "company_id": 64503338,
      "location": null,
      "start_year": 2021,
      "end_year": null,
      "is_current": null,
      "summary": null
    }
  ],
  "db_education": [
    {
      "school": "University of Leeds",
      "school_id": 7244,
      "degree": "PhD",
      "field_of_study": "Computational BioFluid Dynamics",
      "start_year": 1997,
      "end_year": 2000
    },
    {
      "school": "University of Leeds",
      "school_id": 7244,
      "degree": null,
      "field_of_study": null,
      "start_year": 1997,
      "end_year": 2000
    }
  ],
  "education_count": 7,
  "total_positions_count": 165,
  "summary": "I am a Director, Founder, Fractional CTO, Technology Advisor, and University Professor with over 25 years of experience pioneering advanced software solutions across multiple domains and industries. My journey with artificial intelligence began with my PhD in Computational BioFluid Dynamics three decades ago, establishing a foundation that has enabled me to stay at the forefront of AI evolution throughout my career. As generative AI transforms the business landscape in 2026, I combine deep historical perspective with cutting-edge expertise to guide organisations in harnessing these powerful technologies. My approach helps clients boost efficiency, reduce operational friction, and maximise returns on their staff investments through strategic AI implementation. My mission remains clear: propelling technology-focused businesses to excel in highly competitive markets whilst transforming non-technology focused companies into technology-driven organisations. I do this by drawing on my extensive knowledge, expertise, and network of technologists, and by bringing together high-performance technical teams tailored to specific business challenges. As Founder of Indigo Labs, I provide strategic, visionary, and product guidance with AI integration at its core. My work includes roles as Founder, Technology Strategy Advisor, Fractional CTO, University Professor, and Non-Executive Director. I'm particularly keen on mentoring technology leaders who want to become inspirational mentors themselves, and on researching and teaching in the expanding field of artificial intelligence, bridging the gap between academic innovation and practical business applications.",
  "specialties": null,
  "interests": "{Gadgets,swimming,triathlon,film,cooking,climbing}",
  "between_jobs": false,
  "availability_confidence": "high",
  "signals": [
    "signal_fractional",
    "signal_advisor",
    "signal_portfolio_career"
  ],
  "source_signals": [
    "fractional",
    "advisor"
  ],
  "score_details": [
    "signal_fractional:+30",
    "signal_advisor:+18",
    "signal_portfolio_career:+12",
    "function_p3_consulting:+16",
    "seniority_a_founder_clevel:+20",
    "has_email:+3"
  ],
  "lead_score": 99,
  "lead_label": "A+",
  "outreach_ready": true,
  "has_api_enrichment": true,
  "has_education": true,
  "has_skills": true,
  "has_summary": true,
  "api_headline": "The Restless CTO🔹AI Evangelist🔹Co-founder Equiyd🔹Educator🔹Advisor🔹DD🔹Fractional CTO",
  "api_jobTitle": "Director, Founder",
  "api_industry": "Advertising Services",
  "api_location": {
    "country": "GB",
    "countryIso3": null,
    "countryFullName": "United Kingdom",
    "city": "London",
    "state": "England",
    "stateFullName": null,
    "rawLocationString": "Greater London, England, United Kingdom",
    "coordinates": null
  },
  "api_connectionsCount": 4496,
  "api_followersCount": 6362,
  "api_skills": [
    "Leadership",
    "Public Speaking",
    "Software Development",
    "Software Design",
    "Mobile Applications",
    "C#",
    ".NET",
    "Software Engineering",
    "ASP.NET MVC",
    "JavaScript"
  ],
  "api_experience": {
    "work": [
      {
        "startDate": "2014-01-01",
        "endDate": null,
        "company": "Indigo Labs",
        "companyId": {
          "networkId": "indigo-labs-limited",
          "crunchbaseId": null,
          "facebookId": null,
          "twitterId": null
        },
        "title": "Director, Founder",
        "description": "Technology Advisory business that lends its knowledge, expertise and vast network of technologists to companies that wish to stay ahead of the curve in terms of strategy, vision and product roadmap. We help make non-technology focused businesses into technology-driven ones, providing that competitive advantage that less visionary competitors lack. We propel technology-focused businesses to move up the ranks by ensuring the appropriate strategy, roadmap and vision is in place to excel in a fiercely competitive market.",
        "location": "London Area, United Kingdom",
        "logoUrl": "https://assets.outricher.com/pp/profilepic/1490a3c0a1c7cc09e0c24e5c4b777e3d",
        "normalizedSeniority": [
          "Owner"
        ],
        "employmentType": null,
        "jobFunction": null
      },
      {
        "startDate": "2023-03-01",
        "endDate": null,
        "company": "Equiyd",
        "companyId": {
          "networkId": "equiyd",
          "crunchbaseId": null,
          "facebookId": null,
          "twitterId": null
        },
        "title": "Co-founder / CTO",
        "description": "Co-Founder and CTO of Equiyd, where we've been quietly building the most advanced data-first platform for the equestrian industry, and the traction has been incredible. With thousands of users already on board, we're generating vast amounts of valuable data and insights that power our cutting-edge AI engine. This is enabling Equiyd to deliver unprecedented value to horse owners, sports professionals, industry stakeholders, regulators, and organisations across the equestrian world. The future of horse management and equestrian sports is digital, and we're leading that transformation.",
        "location": "United Kingdom",
        "logoUrl": "https://assets.outricher.com/pp/profilepic/f4ae27205718d170d1347cc576d9e046",
        "normalizedSeniority": [
          "Owner",
          "Chief X Officer (CxO)",
          "Executive"
        ],
        "employmentType": [
          "Full-time"
        ],
        "jobFunction": [
          "Sales",
          "Business Development"
        ]
      }
    ],
    "volunteer": [
      {
        "startDate": "2015-01-01",
        "endDate": null,
        "title": "Software Development Mentor",
        "cause": "Education",
        "organization": "Code Academy Club",
        "organizationId": null,
        "description": "Mentoring young people interested in software development to learn programming languages, techniques and computational thinking through a weekly club.",
        "logoUrl": null
      }
    ]
  },
  "api_education": [
    {
      "startDate": "1997-01-01",
      "endDate": "2000-12-31",
      "fieldOfStudy": "Computational BioFluid Dynamics",
      "degreeName": "PhD",
      "school": "University of Leeds",
      "schoolId": {
        "networkId": "university-of-leeds",
        "crunchbaseId": null,
        "facebookId": null,
        "twitterId": null
      },
      "description": null,
      "logoUrl": "https://assets.outricher.com/pp/profilepic/2bc6351fb18de1ce2dce5a8c6d233ddd",
      "grade": null,
      "activities": "Activities and Societies: Room 339a Coffee Club Instituto Cervantes Web master & Social MC"
    },
    {
      "startDate": "1996-01-01",
      "endDate": "1997-12-31",
      "fieldOfStudy": "Computational Fluid Dynamics",
      "degreeName": "MSc",
      "school": "University of Leeds",
      "schoolId": {
        "networkId": "university-of-leeds",
        "crunchbaseId": null,
        "facebookId": null,
        "twitterId": null
      },
      "description": null,
      "logoUrl": "https://assets.outricher.com/pp/profilepic/2bc6351fb18de1ce2dce5a8c6d233ddd",
      "grade": null,
      "activities": null
    }
  ],
  "api__source": "ops01-gateway",
  "api__enriched_at": "2026-07-13T16:42:53.534Z",
  "connections": 4496,
  "num_followers": 6362,
  "profile_summary": "I am a Director, Founder, Fractional CTO, Technology Advisor, and University Professor with over 25 years of experience pioneering advanced software solutions across multiple domains and industries. My journey with artificial intelligence began with my PhD in Computational BioFluid Dynamics three decades ago, establishing a foundation that has enabled me to stay at the forefront of AI evolution throughout my career. As generative AI transforms the business landscape in 2026, I combine deep histo",
  "jobs_count": 34,
  "phone": "+447803927928",
  "gender": "Male",
  "salary_min": 150000,
  "salary_max": 250000,
  "_db_augmented": true,
  "formatted_name": "Alfonso Ferrandez",
  "num_recommenders": null,
  "org": "Indigo Labs Limited",
  "is_incomplete": false,
  "public_experience_available": true,
  "public_education_available": null,
  "top_school": "University of Leeds",
  "top_degree": "PhD",
  "top_field_of_study": "Computational BioFluid Dynamics",
  "corrupt_name": false,
  "merger_shell": false,
  "api_slug": "alfonsoferrandez",
  "api_firstName": "Alfonso",
  "api_lastName": "Ferrandez",
  "api_fullName": "Alfonso Ferrandez",
  "api_jobTitleNormalized": null,
  "api_about": "I am a Director, Founder, Fractional CTO, Technology Advisor, and University Professor with over 25 years of experience pioneering advanced software solutions across multiple domains and industries. My journey with artificial intelligence began with my PhD in Computational BioFluid Dynamics three decades ago, establishing a foundation that has enabled me to stay at the forefront of AI evolution throughout my career. As generative AI transforms the business landscape in 2026, I combine deep historical perspective with cutting-edge expertise to guide organisations in harnessing these powerful technologies. My approach helps clients boost efficiency, reduce operational friction, and maximise returns on their staff investments through strategic AI implementation. My mission remains clear: propelling technology-focused businesses to excel in highly competitive markets whilst transforming non-technology focused companies into technology-driven organisations. I do this by drawing on my extensive knowledge, expertise, and network of technologists, and by bringing together high-performance technical teams tailored to specific business challenges. As Founder of Indigo Labs, I provide strategic, visionary, and product guidance with AI integration at its core. My work includes roles as Founder, Technology Strategy Advisor, Fractional CTO, University Professor, and Non-Executive Director. I'm particularly keen on mentoring technology leaders who want to become inspirational mentors themselves, and on researching and teaching in the expanding field of artificial intelligence, bridging the gap between academic innovation and practical business applications.",
  "api_inferredSalary": {
    "min": 150000,
    "max": 250000
  },
  "api_gender": "Male",
  "api_birthDate": null,
  "api_seniority": {
    "level": null,
    "totalExperienceYears": 24,
    "currentTenureYears": 12,
    "averageTenureYears": 2.11,
    "isDecisionMaker": null
  },
  "api_updatedAt": "2026-07-13T16:42:53.286Z",
  "db_personal_emails": [
    "alfonso.ferrandez@gmail.com",
    "alfonso.ferrandez@doctorlink.com",
    "alfonso.ferrandez@manorf1team.com",
    "alfonso@fruitfulinsights.co.uk"
  ],
  "db_personal_numbers": [
    "+447803927928"
  ],
  "db_new_phones": [
    "+447803927928"
  ],
  "db_github_url": "github.com/drfonz",
  "db_twitter_url": "https://x.com/drfonz",
  "db_facebook_url": "facebook.com/alfonso.ferrandez",
  "db_salary_min": 150000,
  "db_salary_max": 250000,
  "db_new_emails": [
    "alfonso.ferrandez@manorf1team.com",
    "alfonso@fruitfulinsights.co.uk"
  ],
  "db_profile_created_at": "2014-07-09T17:00:00.000Z",
  "db_profile_updated_at": "2026-06-17T19:39:42.218Z",
  "db_profile_activity_at": "2026-03-05T13:26:40.347Z",
  "db_company_description": "At Imperial Business School, we are not just part of a world-leading university, but a world-changing one. As a vital meeting place for science and business, we pursue ideas, pose questions and set out to solve humanity’s biggest challenges. Together, we get closer to the answers. Imperial Business School is where discovery drives development. Where science sparks new ventures. Where theory is fostered, fuelled and furthered. This is where science means business. This means our undergraduate and postgraduate courses are preparing tomorrow’s leaders – by combining technical science with management and leadership science to understand how humanity can find solutions to its pressing problems, take its toughest decisions and lead its greatest organisations. This means that we’re shaping industries, informing government policy and guiding the ethical adoption of new technologies through thought-leadership and by translating pioneering research and making it more accessible. And this means that we’re tackling public health challenges and global climate issues through collaboration and commercial partnerships. Welcome to Imperial Business School. Where science means business.",
  "db_company_type_code": "D",
  "db_company_size_code": "G",
  "db_company_website": "http://www.imperial.ac.uk/business-school",
  "db_company_follower_count": 111677,
  "prior_positions_count": 164,
  "has_prior_positions": true
}

04Which fields matter to whom

The same profile serves different jobs — because everything is stitched together in it at once. You don't need to buy five separate databases for sales, hiring, and analytics.

Sales
Role + company + size + country + email. The key signal is the start date in the role: people in their first 90 days evaluate new tools 3–5× more often.
Recruiting
Career history + education + skills + contacts. You can search for "ex-Revolut backend near Tbilisi" — because the past employer, geo, and role all sit in a single object. No ATS can do that.
Investing · research
Company + size + founded year + hiring signals. A 2-year-old, 50-person company hiring 10+ roles means 100%+ growth per year — invisible in ordinary business directories.
Marketing · ABM
The profile headline is the best personalization trigger: the person has described their own pain, niche, and ICP in a single line. Plus industry, geo, and activity.

05Where the honest boundary is

Maturity is part of the product. Here's what a profile delivers reliably, and what we never promise. This boundary protects trust for years to come.

✓ We guarantee

Name and profile link on every record. Current role and company on virtually every profile. Country, company size, and industry on nearly all. Full career history and education after enrichment. Verified contacts on a solid share of every segment — and we always show you the exact coverage of your pool before you commit.

✗ We don't promise

An email for literally everyone — no honest vendor can. Phones are a rare, high-value bonus channel, not a default. Salary and gender are sparse signals, useful in aggregate. Live-second freshness — the graph updates continuously and on-demand enrichment tops up the rest. And we do not identify the end-consumer users of anyone's app — that isn't in the professional graph.

06The full object — every field

No shortcuts: every field a profile can contain after full processing. The object is built in 4 additive layers — base sample → DB enrichment (db_*) → deep assembly (career + education) → API enrichment (api_*). Sources are never collapsed: base, db_*, and api_* are independent fields, which is why the union reaches 148.

Identity — who this is9 fields
FieldTypeWhat it is
profile_idnumberInternal profile ID — the key for assembly
full_namestringFull name — the primary identifier
first_name / last_namestringFirst and last name — personalization
headlinestringProfile headline (role + company in one line)
public_profile_urlstringProfile link — the deduplication key
profile_summarystring"About" text / bio
formatted_namestringFormatted name (assembly)
is_incompleteboolFlag for an incomplete record
Location — where2 fields
FieldTypeWhat it is
location_namestringCity/region as text
location_country_codestringThe PERSON's country (ISO) — a mandatory geo filter
Career — career and experience15 fields
FieldTypeWhat it is
titlestringCurrent title — the primary ICP field
start_date / end_datedateDates of the current role (null = active) — a "newcomer" signal
is_currentboolConfirmation of the active role
jobs_countnumberNumber of positions in history — career depth
db_experiences[]arrayFull career history (assembly, up to 20): company, role, dates, location, description
current_position_* / total_positions_count / prior_positions_countnumber/strCareer derivatives (current role, position count)
api_experiences[]arrayCareer history from the API (full, when API-enriched)
Education — education7 fields
FieldTypeWhat it is
db_education[]arrayEducation (assembly, up to 10): school, degree, field of study, years
top_school / top_degree / top_field_of_studystringTop school/degree/field of study (derivatives)
education_countnumberNumber of education records
api_education[]arrayEducation from the API (school, degree, field of study, grades)
Company — company13 fields
FieldTypeWhat it is
company_id / company_namestrCurrent employer — ID and name
company_domain / company_websitestringDomain/website — matching in CRM
company_industrystringEmployer industry — vertical targeting
company_employee_count / company_size_codenum/strSize (exact + bucket A…I; the bucket works when the number is hidden)
company_foundednumberFounded year — company maturity
company_type_codestringPublic / private / nonprofit / government
company_descriptionstringCompany description
company_parent_idnumberParent company — subsidiary detection
company_follower_countnumberCompany followers — brand strength
company_countrystringCompany HQ country
Skills · Languages — skills and languages8 fields
FieldTypeWhat it is
skills[]arraySkills for precise role matching
interests / specialtiesstringInterests and specialties (assembly)
api_skills[]arrayFresh skills from the API
api_languages / api_languages_and_proficiencies[]arrayLanguages and proficiency level
api_certifications[]arrayProfessional certifications
Contacts — contacts (waterfall of sources)12 fields
FieldTypeWhat it is
emailstringBest email (work prioritized over personal)
all_emails[]arrayUnion of all known emails
phone / all_phones[]str/arrPhone(s) — a rare but valuable direct channel
personal_emails / emails / personal_phone_numbers[]arrayRaw sources from different tables (Iron #1 — never collapsed)
db_personal_emails / db_new_emails[]arrayDB enrichment: all emails from the database + "new" ones absent from the API (bonus delta)
db_new_phones / db_personal_numbers[]arrayDB enrichment: phones (including ones found beyond the API)
github_emailstringEmail from the linked GitHub (3rd waterfall source)
api_personal_emails / api_personal_numbers[]arrayContacts from the API
Social · Code — social and code8 fields
FieldTypeWhat it is
github_url / db_github_urlstringGitHub — engineering footprint
twitter_url / db_twitter_urlstringX / Twitter
facebook_url / db_facebook_urlstringFacebook
connections / num_followersnumberConnections and followers — reach and activity
Enrichment · Freshness — assembly and freshness14 fields
FieldTypeWhat it is
activity_at / db_profile_activity_atdateLast-activity date — the key reachability signal
profile_created_at / profile_updated_atdateWhen the profile was created/updated
num_recommenders / db_profile_num_recommendersnumberNumber of recommenders — social proof
_db_augmentedboolFlag: profile assembled from the database
db_company_* (founded, description, type, size, parent, website, followers)mixedDB enrichment on the company (employer intelligence)
api_recommendations / api_activities / api_articles / api_groups / api_interests / api_volunteer_work[]arrayContent, activity, groups, volunteer work from the API
api_people_also_viewed / api_similarly_named_profiles[]arraySimilar profiles — lookalike detection
api_accomplishment_* (honors, patents, projects, publications, courses, organisations, test_scores)arrayAccomplishments: awards, patents, publications, projects
Scoring — scoring and signals18 fields
FieldTypeWhat it is
lead_score / lead_labelnum/strComposite score + percentile grade A+/A/B/C
score_details[]array"Why this number" breakdown (e.g. funded:15, hiring:10)
freshness_scorenumberFreshness score (recency of activity)
signal_count / active_signals[]num/arrCount and list of active buying signals (scoring multiplier)
hiring_signal / job_countbool/numCompany is actively hiring + number of open roles
dm_count_at_companynumberDecision-makers/founders found at this company
estimated_revenue / heat_scorenumberEstimated company revenue + heat score
p1_score / p1_label / p1_seniority_tier / p1_function / p1_segments[]mixedPerson-level ICP scoring: score, grade, seniority tier, function, segments
Demographics — demographics (sparse)9 fields
FieldTypeWhat it is
gender / db_gender / api_genderstringGender — DEI analytics (sparse)
salary_min / salary_max / db_salary_* / api_inferred_salarynum/objIncome estimate — budget qualification
api_birth_dateobjectDate of birth (very rare)
Meta — service and sourcing~10 fields
FieldTypeWhat it is
icp_personastringDataset persona tag (e.g. P1)
anchor_company / anchor_company_id / anchor_prioritystringThe anchor company the lead was found through, and its tier
api_public_identifier / api_first_name / api_last_name / api_full_name / api_headlinestringDuplicate fields from the API, kept separately (Iron #1 — never collapsed)
api_extraobjectNested object: github/twitter/facebook profile id, website
Why so many fields for one person? An Iron Rule of our pipeline: sources are never collapsed. If both the database and the API have an email, that's two distinct fields (db_personal_emails and api_personal_emails), not one overwritten value. That way the client gets the maximum and can see where each value came from. This is exactly why the field union reaches 148, while ~116 are filled on average — the rest depends on what turned up for the specific person.
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MEASURED · Outricher data · 2026-06-28