A Connected Architecture for U.S. Corp-to-Corp Staffing: Representation, Rate Traceability, and Workforce Operations
The architecture described here is targeted at the U.S. market for corp-to-corp (C2C) staffing services. Requirements, representation agreements and negotiation of the rates to be paid are frequently spread out over email threads and messaging groups. Approach. A practitioner-informed conceptual design for such recruitment is developed here from the founder’s descriptions of his current workflow, supplemented by a focused narrative discussion of recruitment accountability, explainable AI and human oversight. The design here comprises six stages. Architecture. A candidate signs the right-to-represent (RTR) agreement(s) for that candidate’s submission and the employing organization acknowledges representation of the candidate(s) by the submitting organization(s). Where a subsequent rate change is negotiated with the candidate a new signature from that candidate is required. Unreadable screenshots require human review to evaluate agreement. A mismatch between the entered hours on a timesheet and the corresponding evidence uploaded by the employee (e.g. a photo of a time card) to verify those hours will block approval and, consequently, invoice transmission until that mismatch has been corrected by the employee. Status and Limitations. All of the features described here are under current development by the founder and there are currently bugs to be fixed. As far as has been reported, the integrated workflow described here has not yet undergone a structured evaluation and the diagrams provide logical components and controls to be developed and verified as required against a variety of test cases rather than a verified deployment topology. The paper reports no measured efficiency improvements, accuracy improvements, placement improvements or fairness improvements as yet.
Authors
- Sai Pavan Kumar Gopularam
Publication Details
- Journal
- International Journal of Sustainability and Innovation in Engineering
- Published
- 2026-11-10
- DOI
- https://doi.org/10.56830/ijsie202612
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00