Want to build something awesome with our Festival API?

Build our founder & investor scoring rubric into your own application.

Existing profiles are free to look up. Pay to score new ones.

Everything the API returns is public profile data — exactly what a visitor sees on the site. It never returns emails, phone numbers, or anything a person marked private.

A profile lookup returns the whole public picture:

Composite + individual founder & investor scores — each dimension's score plus the person's percentile rank, and a current / past / never status marker.
Score breakdown — the individual founder and investor signals behind each score, each with a confidence level and human-confirmation status.
Credibility radar — the spider-graph axes (technical, traction, operator, domain, GTM for founders; portfolio, exits, firm, experience, capital for investors), percentile-ranked, with the evidence behind each axis.
Peer matrix — who's most like, most complementary to, and least like this person.
Badges, industries & outcomes — achievement badges, normalized industry tags, and traction facts (IPO / acquisition / unicorn).
Investor focus — stage focus, industry focus, check size, and whether they lead rounds.
Guidance — a plain-language “what they likely need” summary and recommended priorities tagged by category.
Identity — name, company (+ link), profile photo and location for claimed profiles, signal quality, and claimed status.

Plus endpoints to explore the whole dataset:

Resolve a name (+ company) to ranked LinkedIn candidates.
Search scored people by name or company.
Leaderboard — filter by role, industry, stage, outcome, badges, amount raised, and team size; paginated.
Events — published qualifying events.
Industries — the canonical industry taxonomy.

Cost per profile:

FREE

Existing profiles

$0.60

New profiles

Endpoints

GET/api/v1/resolve?name=&company=Name → ranked LinkedIn candidatesFree

GET/api/v1/score?linkedin_url=Full public profile (cached)Free

POST/api/v1/scoreScore a new person on demandCredits

GET/api/v1/search?q=Search scored people by name / companyFree

GET/api/v1/leaderboardFilterable, paginated leaderboardFree

GET/api/v1/eventsPublished eventsFree

GET/api/v1/events/{slug}One published eventFree

GET

Example profile response

Abbreviated GET /api/v1/score response — arrays trimmed for brevity.

{
  "linkedin_url": "https://www.linkedin.com/in/example",
  "full_name": "Jane Q Founder",
  "company_name": "Acme", "company_url": "https://acme.com",
  "profile_href": "/profile/jane", "avatar_url": "https://…", "claimed": true,
  "location": { "city": "San Francisco", "region": "CA", "country": "USA" },
  "signal_quality": "high",
  "scores": {
    "overall":  { "score": 530, "percentile": 92 },
    "founder":  { "score": 410, "percentile": 95 },
    "investor": { "score": 120, "percentile": 61 }
  },
  "founder_status": "current", "investor_status": "past",
  "badges": ["yc", "unicorn", "raised"],
  "canonical_industries": ["ai-ml", "fintech"],
  "outcome": { "had_ipo": false, "had_acquisition": true, "is_unicorn": true,
               "ipo_market_cap_usd": null, "acquisition_price_usd": 250000000 },
  "investor": { "stage_focus": ["seed","series-a"], "industry_focus": ["fintech"],
                "leads_rounds": true, "check_size": { "min_usd": 250000, "max_usd": 1000000 } },
  "neo": { "on_neo": true, "slug": "jane-q" },
  "founder_rows": [ { "reason": "Scaled to 200 employees",
                      "confidence": 90, "status": "confirmed" } ],
  "what_you_likely_need": { "text": "Raise a Series A.", "status": "likely", "confidence": 80 },
  "current_priorities": [ { "id": "p1", "text": "Hire a VP Eng",
                            "category": "hiring", "rating": 4, "private": false } ],
  "credibility": {
    "founder": [ { "key": "technical", "label": "Technical Depth", "axis_label": "Technical",
                   "score": 88, "coverage": true,
                   "evidence": [ { "reason": "Built core ML platform" } ] } ],
    "investor": null
  },
  "matrix": {
    "founder": {
      "similar":    [ { "full_name": "Sam O", "profile_href": "/profile/sam",
                        "avatar_url": "https://…", "display_score": 480 } ],
      "complement": [ /* … */ ],
      "opposite":   [ /* … */ ]
    },
    "investor": null
  },
  "scored_at": "2026-05-20T12:00:00.000Z", "cached": true,
  "cost": { "charged_cents": 0, "basis": "cached" }
}

Here's how to get started:

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