The Problem
Your current path to compliance doesn’t work.
Fragmented source systems
Compensation data lives in Workday for some countries, SAP for others, local payroll engines for the rest. No two use the same field names, currencies, or pay component structures.
Manual extraction and normalization
Your team exports CSVs from each system, manually maps compensation components, converts currencies, and pastes into a master spreadsheet. Every pay cycle. For every country.
Audit Exposure
An auditor will ask: how did you derive this number? With a spreadsheet, the answer is “someone typed it.” With datascalehr, every field has a complete lineage trace from source to output.
How datascalehr solves this
Audit-proof pay equity data from your existing systems. No replacement. No 2-year project.
datascalehr’s Context Layer connects to your source systems, normalizes compensation data across jurisdictions, and produces audit-ready output. Your payroll specialists drive the process. No IT project. No consultants mapping spreadsheets.
1: Connect your source systems
Upload sample files or connect via API. KMod™ has seen 7,000+ schemas across 150+ countries. It recognizes your data structure and predicts field mappings instantly.
2: Normalize across jurisdictions
German base salary, French 13th-month pay, UK pension contributions. KMod™ understands jurisdiction-specific compensation components and normalizes them into comparable categories.
3: Produce audit-proof output
Every data point has a full lineage trace: where it came from, how it was transformed, who approved the mapping. The output is formatted for your specific compliance framework.
4: Stay current automatically
When a payroll provider changes their format or a regulation changes a field requirement, the Context Layer adapts. No maintenance backlog. No emergency rebuild.
The Context Layer: why datascalehr can do this and consultants can’t.
KMod™ is a predictive AI engine trained on 1.5M+ validated mapping decisions. It doesn’t guess. It identifies the correct transformation from a known set of valid mappings — 100% accuracy, no hallucinations. When your payroll specialist in Munich confirms a mapping at 9:00 AM, a colleague in Vienna benefits at 9:01 AM. Knowledge compounds with every deployment.
1.5M+
Validated mappings
150+
Countries
1,000+
Live connectors
100%
AI accuracy (no hallucinations)
Production Results
Benchmarked by the world’s largest payroll operators.
75%
Less migration effort
HCM system migration reduced from 12 months to 3 months in project person-days. Implementation partners deliver faster. Your team gets payroll live sooner.
2 hours
Per country to deploy
1 day of training, then 2 hours per country. Your payroll specialist uploads data, reviews AI-predicted mappings, and confirms. No IT project.
16x
Data comparison
Europe’s #1 payroll provider cut reconciliation time from 4 hours to 15 minutes per cycle.
90%
Of the work done for you
KMod does 90% of the mapping work automatically. Your payroll specialist confirms and corrects the rest. No developers. No file specs.
June 2026 is not a deadline you can push.
See what compliance actually costs with traditional integration vs. datascalehr. Use the calculator above, or bring your sample data and we’ll show you results in the meeting.
Trusted by the World’s Best Payroll Operators
ROI Calculator
What does this actually cost? Less than you think.
Most teams expect years and millions. The reality: 1 day of training, then 2 hours per country.
Assumptions
Traditional: $75–100K per country, 4–6 weeks per country (sequential), $15K/yr/country maintenance.
datascalehr: 1 day training (one-time) + 2 hours per country + IT setup (1 day for Pay Transparency).KMod™ has 1.5M+ validated mappings across 150+ countries. Predictive AI accuracy — no hallucinations.
Costs shown in the datascalehr column reflect your organization's remaining implementation effort (team time, familiarization, IT setup) — not datascalehr platform licensing. Subscription pricing is based on number of countries and connectors and is quoted separately. The savings figure represents implementation and maintenance cost avoidance before licensing.
