The structure and wiring
of your enterprise

The structured layer underneath everything your enterprise does — every job, task, subtask, and workflow, captured live and kept current. It's the foundation AI agents, workforce planning, and compliance all need to actually work, sourced from one place instead of stitched together across systems.

Job architectures and skills taxonomies describe roles and capabilities. A Work Architecture describes the work itself — what gets done, how it flows, who and what does it. Job and skills data sit inside it, but the architecture goes deeper: down to tasks, workflows, and the context AI needs to operate.

Any enterprise deploying AI at scale, planning workforce strategy across changing work, or running compliance on regulated workflows. If your AI deployments stall at the pilot stage, your workforce data lives in five systems, or your auditors ask questions you can't answer in real time — this is the missing layer.

Reejig builds your initial Work Architecture from existing data (HRIS, job descriptions, whatever you have) in days or weeks, not the multi-year consulting engagement traditional approaches require. From there, it stays current automatically as work evolves.

Reejig scores every task against the AI you've already approved, so you know exactly what's deployable today, what needs governance first, and what should stay with people. Every AI decision runs on real work data, not vendor pitches or theoretical potential.