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GET
Confidence band + data-completeness diagnostics for a score.
A composite_score of 67 sounds the same whether it was computed on full data or half-empty fetcher results. This endpoint exposes the difference: data completeness, failed fetchers, and which signals fell back to neutral defaults.

When to use it

  • Before trusting a score for a high-stakes decision.
  • To render a “confidence” pill next to the score in your UI.
  • To explain to a stakeholder why a small / private company has a directional rather than precise score.

The three bands

Response shape

For comparison, a thinly-covered domain:

missing_signals semantics

A signal is “missing” if it’s currently scoring at the neutral fallback (≈ 50 / 100). This is not the same as a zero — neutral 50 means “we have no real data, so we’re not penalizing or rewarding.” A long missing list pulls the composite toward 50.

How completeness is computed

A weighted ratio of “signals with real underlying data” / “signals applicable to the target’s profile”. Established companies have different applicable signals than growth companies (some venture-stage signals are N/A for mature firms), so the denominator is profile-aware.

Authorizations

X-API-Key
string
header
required

Live keys are prefixed ki_live_, test keys ki_test_. Issue + revoke keys at https://console.keplerinsights.us. Never embed a key in client-side code — every endpoint is backend-to-API only.

Path Parameters

domain
string
required

Bare hostname. Strips a leading www. and any URL scheme automatically.

Response

Confidence breakdown.

mode
string
domain
string
scored_at
string<date-time>
band
enum<string>
Available options:
high,
medium,
directional
completeness_pct
integer
Required range: 0 <= x <= 100
failed_fetchers
enum<string>[]
Available options:
firmographic,
people,
web,
news
data_warnings
string[]
missing_signals
string[]

Signals currently scoring at the neutral 50 fallback.