HubSpot
Salesforce
Pipedrive
Intercom
Mailchimp
Enforcement by reconciliation
Insycle does not sit in the write path; CRMs accept every write. Enforcement is infrastructure-style reconvergence against declared state, much like Kubernetes restores intended configuration after drift.
PLATFORM OVERVIEW
Your strategy, running as a system.
Declare how your CRM data should be. Insycle evaluates every record against it, corrects what diverges, and shows you what is drifting, cycle after cycle, whoever is writing.
Consistent across multiple CRMsContinuous reconciliationPreview and full audit trail
Declared state · continuous reconciliation
- 01
Blueprints Declare
What right is
- 02
Every ingestion Evaluate
Conformance or drift
- 03
Data Logic Correct
Reconverge to standard
- 04
Observability Watch
Coverage steady · drift ↓
Watch feeds the next declaration and cycle
Enforcement by continuous reconciliation The way modern infrastructure holds itself to declared state.
Continuous reconciliation
How a record stays right.
A record arrives from an import, sync, form fill, rep edit, or agent write, and the CRM accepts it. Insycle evaluates it against your Blueprints: conforming records count toward coverage; diverging records surface as drift. Data Logic corrects the record on a schedule, through existing CRM automation, or on demand with preview. Observability keeps watching every later write, so when another process changes the field, the next cycle catches the divergence and reconverges it to the declared standard.
A filter catches only the wrong you enumerated. Here, right is declared once, and everything outside it keeps revealing itself.
Declare
Blueprints, your strategy, as data.
Blueprints are versioned tables that define what correct CRM data should look like. Canonical countries and states. Job-title seniority mappings. Territory assignment logic. Lifecycle definitions. Lead-source taxonomies.
- Declarative. A Blueprint says what right is; it does not script how to fix wrong. Add a row and the standard grows.
- Versioned. Every change is tracked, so “what did the strategy say in March?” has an answer.
- Yours. The tables encode decisions only your team can make, not generic checks that miss business-specific intent.
- One strategy, reusable across CRMs. Bind the Blueprint to the appropriate fields in each connected environment so the same business standard can be applied without duplicating the strategy.
Blueprint · Territory strategy · v12
StatusActive standardVersioned
| Country | Employee band | Territory | Team |
|---|---|---|---|
| United States | 1-200 | NA · SMB | Velocity |
| United States | 201-1,000 | NA · MM | Commercial |
| Germany | Any | DACH | EMEA |
| United Kingdom | Any | UKI | EMEA |
12 versionsHubSpot + Salesforce bindings
Enforce
Data Logic, your strategy, enforced.
Data Logic binds a Blueprint to CRM fields, scopes the records, previews the result, and applies the declared standard. Run it on a schedule, launch it on demand, or trigger it through supported CRM automation, including HubSpot Workflows and Salesforce Flow.
Preview before run
See every proposed field change and error before anything lands in the CRM.
Full audit trail
Every run, record, and value is captured before and after, available for download, with the Run ID stamped on affected records.
Update conditions per field
Always corrects disagreements with the Blueprint. Field Empty enriches without overwriting deliberate values.
Data Logic · Preview
Blueprint column Territory
CRM field Account Territory
| Acme Software | West | NA · MM | Correct |
| Northstar GmbH | , | DACH | Fill empty |
1,842 proposed updatesNo CRM changes made
Why not put this in CRM workflows?
Because strategy should be one reviewable, versioned table, not branch logic scattered across automation, code, and spreadsheets.
Change the Blueprint version and the template, schedule, and triggers stay untouched. You can always answer, “What did the logic say at the time?” This does not replace CRM automation: a HubSpot Workflow or Salesforce Flow can trigger the Data Logic template, while the Blueprint holds the strategy it applies. And unlike workflows that simply execute logic, Observability measures whether your data continues to conform, showing coverage, gaps, and drift over time.
Data Logic in depthWatch
Observability, your strategy, watched.
Observability continuously measures whether governed CRM records still match the standards declared in your Blueprints. It is not a report someone remembers to run. It is a watch that never ends.
- Coverage. Of the records you govern, the share that match your standards, the number that grows as Blueprints expand.
- Drift. What diverges from the standard, surfaced on the next cycle, whatever wrote it. Persistent drift signals another process owns the field; attribution remains the team’s investigation.
- Trends. Integrity over time, per object and standard, the visible difference between “we cleaned it once” and “it is still right.”
Observability · Companies
Coverage
94.6%
+1.8 pts
Drifted records
318
↓ 42%
Standards watched
12
Active
6 cycles agoCurrent
CoverageDrift
| Standard | Coverage | Drift |
|---|---|---|
| Territory mapping | 97.2% | 54 |
| Country canonicalization | 95.8% | 81 |
| Lifecycle definition | 91.0% | 183 |
Capabilities connected to the system
The instruments of integrity.
The operations teams come to Insycle for, sync-safe deduplication, standardization, cleansing, controlled imports, associations, and routing, all running on the same machinery: one filter engine, reusable templates, preview, one automation layer, and one audit trail. Every fix can become a standard; every standard watches itself from then on.
Fix
Data Management
Explore the hub
Activate
RevOps Acceleration
Explore the hub
Come for the fix. Stay for the system that makes it the last time.
Where quality fits
Measured by quality. Maintained by integrity.
Health Assessment
The snapshot
Scores your data’s current state, the lab result and the place everyone starts.
Data Integrity
The operating system
Keeps the score from decaying through the declared standard, continuous enforcement, and watch.
Quality is the output metric. Integrity is the operating system.
Built as infrastructure
Built to be trusted with your CRM.
SOC 2 Type II
Controls independently examined.
Granular permissions
Approvals and access aligned to team roles.
Full audit trail
Every run, record, and before-and-after value.
Versioned Blueprints
The history of what the standard said.
Maintained reference data
Postal, geographic, and naming data updated for you.
Trusted by 700+ customers
Built through real CRM operations at scale.
Common questions
The platform, explained.
Does Insycle sit in the write path of my CRM?
No. Insycle does not sit between your users, automation, and CRM or block incoming writes. It enforces standards through continuous reconciliation: whenever data is ingested, records are evaluated against your Blueprints. Data Logic reconverges records to the declared standard when its template runs, on demand, on a schedule, or from a CRM trigger. Your CRM continues operating normally throughout.
How is this different from a data quality tool?
Data quality tools typically assess the current state of your data through predefined checks. Insycle evaluates records against your declared strategy: your canonical values, lifecycle definitions, territory logic, scoring models, and other business-specific standards.
A record can pass common quality checks while still violating the way your business says it should be interpreted. Data quality is the output metric; data integrity is the operating system that maintains it.
What is the difference between the Health Assessment and Data Integrity?
They differ in what they measure against and what they do about it. The Health Assessment scores your data against general notions of clean, formatting issues, missing fields, duplicates, and tracks that score over time. Data Integrity evaluates records against your declared strategy, your territories, lifecycle definitions, canonical values, then corrects what diverges and watches whether it holds. A record can score healthy and still be wrong by your own definition of right. One measures quality; the other maintains integrity.
What happens when something else keeps rewriting a field?
The CRM accepts the write, and the next ingestion evaluates the record against its Blueprint and surfaces the divergence as drift. Data Logic can correct it when the template runs and its update conditions permit.
If the field returns to drift after correction, that recurrence becomes the finding. It signals that another person or process may be rewriting the field, while Observability identifies the affected field, records, and time window your team should investigate.
Do I have to rebuild my data management setup to use Data Integrity?
No. The Insycle tools teams already use for deduplication, standardization, cleansing, controlled imports, associations, bulk updates, and routing continue working from day one.
Data Integrity connects that work into a standing system. As recurring standards and decisions are formalized in Blueprints, Data Logic applies them consistently and Observability measures whether the results continue to hold.
Put the strategy against the records
Connect your CRM and watch it evaluated against a strategy within the hour.
Start with one Blueprint, preview how Data Logic would apply it, and see coverage and drift become measurable.
Build the internal case
See why governed CRM data matters for AI.
Learn how reliable CRM context improves agent performance, limits machine-speed errors, and makes the AI you already bought work better.
Explore CRM data for AI