Qore's GenAI agents work inside your existing CRM to continuously validate, refresh, and enrich accounts in real time — no manual cleanup sprints, no third-party data subscriptions, no migration.
Every record moves through the same governed pipeline — captured, standardized, deduplicated, and enriched — before anything is written back to your CRM.
RPA pulls data straight from source systems — no manual entry, no missed fields.
Names, addresses, and codes normalized to one format — no more three spellings for one company.
Duplicates are clustered and merged into one golden record — every merge reviewed by a human.
Fields are filled and refreshed against live signals — kept current, not just present.
Each row is a specific way CRM data breaks down, the capability that fixes it, and what changes once it's running.
Anyone whose pipeline accuracy and campaign targeting depend on the data underneath it being right.
Particularly interested in the audit trail and change-log capability — every change logged with rationale, not silently overwritten.
Broadly: any mid-to-large organization where manual, data-heavy processes are the bottleneck standing between reps and selling.
Most teams run continuous validation once it's live. But if you're starting from a large backlog, or only need periodic passes, we scope that too.
Records are validated and refreshed continuously as things change — not on a weekly or monthly cleanup cycle. This is how most of the product runs day to day.
For a one-time backlog, a data migration, or teams that only need a periodic pass rather than continuous monitoring — the same pipeline runs as a scoped batch job instead.
Connect directly to Qore's enrichment data via MCP — no new portal, no custom integration code. Get an API key, add one config block, and your AI assistant can look up company hierarchy and verified addresses on the spot.
No. Qore's agents work natively inside your existing CRM — Salesforce, Microsoft Dynamics, Oracle CRM, HubSpot, and others. No migration, no replacement, no workflow disruption for your team.
Records are validated and refreshed continuously as things change — not on a weekly or monthly cleanup cycle. Drift is caught as it happens, not weeks later.
That's available too. For a large backlog or a data migration, the same capture → standardize → dedupe → enrich pipeline runs as a scoped batch job instead of continuous monitoring.
Yes, especially for merges and hierarchy changes, which are hard to reverse cleanly. AI does the heavy lifting on speed and scale; a human keeps the accuracy and the accountability.
Every change is logged with rationale, not silently overwritten — so Data Governance teams have a documented record for each decision.