Your AI agents can’t operate on payroll data they can’t reach.
The context layer for global HCM data.
datascalehr normalizes fragmented payroll data across 150+ countries — so your systems, agents, and providers work together. 1.5M validated mappings. 1,000+ live connectors. 100% AI accuracy.
Trusted by the world’s best payroll operators
AI payroll Agent
Upload any file, from anywhere
No coding and no configuration means no technical debt.
In the old days, you’d have to modify the data, translate it, transform it…
datascalehr removes all those steps for us and does it automatically.
Reconcile instantly. Scale infinitely. This is a never-before-seen payroll solution. Allow us to explain.
Your Products and Services
HRIS
Frontend Payroll
Onboarding
Call Center
ESS
Early Wage Access
Money Movement
Compliance
Analytics
One global API to integrate your products with any payroll engines.
Network of In-Country Payroll Providers
Hard-to-believe performance.
Faster
Client provisioning and setup*
Faster
Payroll implementation (sales to cash)*
Faster
Daily payroll operations*
Faster
Time-to-productivity for new payroll admins*
*Benchmarks independently performed by one of the world’s largest payroll operator with no input or oversight from datascalehr. Scope: 5 countries, 3 continents, 5k employees. Provisioning & setup refers to the time needed to create the infrastructure for a new payroll client. Daily payroll operations includes monthly workflows such as data updates & payroll reconciliations.
The context layer in action.
Countries Connected
Fields Mapped
API connectors Created
Countries currently mapped by KMod™. This number increases regularly as our clients upload files for new countries or connect to new payroll providers.
Total number of unique data fields that are currently mapped by KMod™. This number increases everyday as our clients upload new files or map to new systems.
Number of complete end-to-end mapping, validations and transformations mapped by KMod™. For example, this could be a Workday PECI file from a client, validated and transformed to connect with a Payroll Engine in Ghana.
Every mapping decision compounds. The context layer learns from every deployment, every correction, every country.
Averaging:
370
Total Fields Per Country
150
Fields Per G2N
60
Fields Per Export File
30
Fields Per Input File
30
GL Mappings Per Inferface
The reason we can do this is because we support a fundamentally new architecture that is based around machine learning. This enables you to connect from anywhere to anywhere in minutes, with no coding ever.
10x efficiency at a quarter of the cost
On average, we cost a quarter of what it would take for you to build it yourself, with performance that is 10x better.