Data coverage
Coverage is useful only when it matches your market, buyer roles, required fields, and freshness threshold. Our operating principle is to expose those conditions before a result is approved.
Mission
Company discovery should show why an account matched, which evidence was available, and where the record remains uncertain. That clarity lets RevOps and sales leaders build a repeatable acceptance policy instead of trusting an opaque score.
We focus on the work between an ICP hypothesis and a responsible outreach decision: identity resolution, role relevance, field provenance, freshness, exclusions, and human review.
Point of view
A missing field should not quietly become an inference. A weak signal should not masquerade as intent. The workflow preserves “unknown,” “unverified,” and “config-dependent” states so a reviewer knows what can safely move forward.
This standard is especially important when contact data, regional privacy expectations, and email deliverability intersect.
Research culture
Convert adjectives such as “high growth” into observable, time-bounded signals.
Evidence belongs beside the field it supports, not buried in a final methodology note.
Conflicting identity or role evidence remains visible until a reviewer resolves it.
A good match still requires message review, opt-out handling, and regional compliance checks.
Working environment
Begin with a small cohort
Write the expected company identities and rejection reasons before the run. Then compare output field by field, document stale or conflicting evidence, and decide which failures should stop a record from reaching a representative. This produces a coverage standard grounded in your market instead of a universal headline number.
npx -y @okki-global/okki-go-taroball