Introducing SignalWork™: See the Cost of Every Workforce Choice Before You Make It
Most enterprises plan their workforce across an applicant tracking system, an HRIS, and finance, none of which talk to each other or offer a predictive view. As AI spend rises, leaders are failing to measure token cost against the outcome it was supposed to produce. Companies are also cutting roles for full automation without ever measuring what the person in them contributed. The relationships and judgment calls often leave with that person, and the workflows built around them can break.
Signal Labs set out to optimize the enterprise workforce and give leaders a way better plan before making those decisions. Today we’re excited to launch SignalWork™, a work and attention allocation platform for CHROs, CIOs, CTOs, and CEOs. It runs on institutional world models, so leaders can weigh the cost and consequences of assigning work to people or to AI agents before they commit resources. SignalOS™ customers Infinite and VetJobs will be the first to use it. Jamie Dale of VetJobs says the team has already seen proof that SignalWork eases the work of grant compliance by 50%.
What SignalWork does for you
- Rehearse before you commit: Simulate different ways to allocate work across humans and agents, allow leaders to see the expected costs, dependencies, and risks of each option first. Decision Memory then compares each prediction with the observed outcome, so better decisions are made over time.
- One ledger for people and agents: AI agents are tracked next to human roles with the same cost and governance controls, so you can preview an agent’s impact before you deploy it.
- Spend tied to outcomes: Monitor consumption and spending thresholds in the context of the work being performed, so AI cost is measured against what it produces.
- Works with your current systems: SignalWork connects BrassRing, Workday, and SAP with outside data such as news, weather, and government planning, so you get one view of the workforce.
From our founder
“You’re running a mix of people and AI agents against goals that used to be staffed by people alone. You need to understand how that work fits together and what happens when you change who does it. Institutional world models let us rehearse those choices before committing resources. SignalWork turns that understanding into allocation and execution, within the enterprise’s rules, and learns from what actually happens.”
Request a demo at signallabs.ai/signalwork to see SignalWork in action.
Signal Labs Launches SignalWork, a Work and Attention Allocation Platform for the Human-AI Workforce