Define
Translate the commercial question into explicit include/exclude criteria, required evidence, buyer roles, output fields and acceptance rules.
From commercial question to decision-ready intelligence. Infinizy combines appropriate data, business events, targeted web research, AI-assisted workflows and human review—with qualification, evidence, interpretation and limitations kept visible.
Translate the commercial question into explicit include/exclude criteria, required evidence, buyer roles, output fields and acceptance rules.
Build and resolve the account universe, route each field to appropriate sources, detect relevant developments and map buyers.
Check important evidence, entity relationships, freshness, buyer relevance and contact status. Keep uncertainty visible instead of forcing a conclusion.
Deliver structured intelligence with context, capture acceptance or rejection reasons, and refine the model before scaling or refreshing.
The exact workflow changes by project, but these disciplines remain consistent.
Turn broad language such as “enterprise,” “founder-led,” “uses X” or “fast-growing” into observable rules and evidence requirements.
Define which source types support each field, plus fallback routes, freshness expectations and confidence rules.
Test deliberately different accounts before promising a large build, especially when the requirement is new or data availability is uncertain.
Normalize brands, legal entities, parents, subsidiaries, locations and duplicates before qualification and buyer mapping.
Accounts that fail the model should carry a reason. That makes the qualification logic inspectable and easier to refine.
Where the engagement requires it, retain source references, dates, confidence, interpretation and limitations alongside the structured fields.
Verified or source-supported information about the company, buyer or environment.
A dated business event or condition that may affect commercial relevance.
Our judgment about how the evidence may connect to the buyer's commercial objective.
A recommended next step—not a promise that the account will buy.
Automation and AI can accelerate discovery, extraction, classification and first-pass synthesis. Human review remains important where entity resolution, commercial relevance, buyer roles or final interpretation are ambiguous.
A sample or pilot should make the quality standard visible before a larger engagement.