
A unified data backbone powering labor intelligence, employability, and digital governance.
RestartUs provides a Data-as-a-Service (DaaS) infrastructure that integrates workforce, education, employer, and economic datasets into one unified national data fabric.
Unlike fragmented systems built around isolated databases, RestartUs delivers continuous, validated, and interoperable labor data supporting real-time intelligence for:
The platform functions as a central data engine that powers AI-driven decision-making and workforce optimization across institutions and regions.

RestartUs structures national workforce data across five interconnected layers, ensuring precision, traceability, and policy value.

| Data Layer | Description | Policy & Industry Impact |
|---|---|---|
| Identity & Profiles | Users, credentials, background, verification | Trust, authentication, fraud prevention |
| Skills & Education | Courses, certifications, pathways, learning outcomes | Training aligned to labor demand |
| Employment & Labor Demand | Job listings, employer needs, sector demand trends | Workforce planning & economic clusters |
| Mobility & Transitions | Job changes, migration flows, cross-regional pathways | Talent movement & resource allocation |
| Performance & Outcomes | Success rates, reskilling ROI, productivity metrics | Evidence-based social and labor policy |
This layered architecture supports data sovereignty, transparency, and auditability—required for national systems.
Most platforms store data. RestartUs correlates and activates it.
Our system continuously cross-links:
* Profiles ↔ verified education + credentials
* Employer demand ↔ sector growth projections
* Regional needs ↔ service capacity
* Skill gaps ↔ mapped training pathways
* Social support ↔ employment outcomes
This generates live labor intelligence, not static reports.
Example:
If demand increases for healthcare technicians in a region, the platform:
1. Maps available local talent
2. Identifies missing skills
3. Routes users to targeted training providers
4. Predicts placement success rates
5. Alerts public agencies to workforce gaps
This shifts labor policy from reactive to predictive governance.

API connections to public systems, welfare, education, HR, payroll
Standardized schemas and structured data models
Public cloud, private cloud, or sovereign hosting options
Streaming data pipelines instead of periodic uploads
Continuous enrichment and validation layers
Fraud-resistant identity and credential verification
Localized hosting aligned to national compliance
Tier-based access controls for different agencies
Regulatory audit dashboards with full traceability
| Outcome | Measurable Result |
|---|---|
| Reduced skills mismatch | Training aligned to economic needs |
| Higher labor mobility | Verified digital work records across regions |
| Faster job placements | Autonomous matching replaces manual workflows |
| Optimized public spending | Data-driven allocation of training funds |
| Stronger economic resilience | Future-skills forecasting for national planning |
DaaS is not a reporting tool—it is a core component of modern digital government and enterprise infrastructure.