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Centralized Company & Contact Database

Centralized Company & Contact Database

Most go-to-market teams suffer from fragmented, stale, and duplicate company and contact data spread across CRM, email, enrichment feeds, and spreadsheets—making routing, segmentation, and forecasting unreliable. Creso’s Centralized Company & Contact Database consolidates tenant-isolated company and person records, automatically dedupes and enriches them, and exposes a single, always-current knowledge graph with field-level provenance and freshness scoring so every team works from one trusted source of truth.

  • check Faster integrations, lower maintenance

    Creso provides a stable, API-first data abstraction layer that pulls from and automatically resolves multiple data sources. No more enrichment hacked together. Developers ship integrations in days instead of weeks and avoid brittle glue code for pagination, retries, and schema drift.

  • check Territory mastery and higher win rates

    Sales leaders and AEs get complete market mapping, accurate firmographics, and relationship graphs that reveal untouched accounts, buyer committees, and warm intro paths—reducing research time, improving multi-threading, and shortening sales cycles.

  • check Data governance, compliance, and measurable quality

    RevOps and data stewards gain role-based controls, per-field provenance, freshness badges, and a stewardship UI for merge/split workflows, plus dashboards to quantify data health and ROI.

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Creso’s Centralized Company & Contact Database is a tenant-isolated repository that unifies companies and people into a single, authoritative dataset. It is seeded from all data on the Internet and incrementally enriched with secondary sources and customer- specific CRM layers. Every attribute stores source, timestamp, and a FreshnessScore so teams can always tell what to trust. The platform supports email matching, social profile linking, and optional email/calendar ingestion for private relationship signals, enabling a practical knowledge graph that links people, roles, hierarchies, and interactions.

Under the hood, deterministic and probabilistic identity resolution clusters records into golden company and person entities. A freshness & quality Engine calculates per-field freshness scores and coverage metrics. The result is automatic auto-merges at high confidence, a fallback Needs-Review queue for human-in-the-loop decisions, and an audit trail for compliance and traceability.

Operationally, the database is built to plug into existing GTM systems: low-latency indexed search and faceted filters enable rapid list-building by industry, size, tech- stack, and seniority. Bidirectional syncs keep downstream CRMs consistent while honoring lock policies. Webhooks notify downstream systems of creates/updates/merges. You get saved segments, pitch primers, and list exports— delivering faster time-to-first-meeting, cleaner pipelines, and predictable forecasting without long IT projects.

How It Works

1

Tenant Provisioning & Security

One isolated tenant is created per customer with row-level security, encrypted storage, and SSO (SAML/OIDC) roles so data access, residency, and audit requirements are enforced from day one.

2

Seeding & Enrichment

The tenant is initially seeded with data based on their GTM strategy with each field tagged by source and timestamp.

3

Identity Resolution & Knowledge Graph Assembly

Deterministic and probabilistic matching cluster records into entities using configurable keys and confidence thresholds, then assemble them into a knowledge graph linking companies, people, hierarchies, and relationship signals.

4

Stewardship, Sync & Observability

Data stewards use a Review Queue and field-level lineage to merge/split and set survivorship rules while bidirectional syncs, webhooks, consent flags, and quality dashboards that keep downstream systems accurate.