Signal Labs has announced SignalWork, a work allocation platform built for CHROs, CIOs, CTOs, and CEOs who need to know not just what AI can do for their workforce, but what it should do, and at what cost. Rather than a management or reporting tool, SignalWork is built to allocate work across people and AI agents on a single ledger and execute authorized actions within enterprise-defined controls.
Signal Labs has launched SignalWork, a work and attention allocation platform for the human-AI workforce.
The platform is built for CHROs, CIOs, CTOs and CEOs managing a mix of people and AI agents against business goals.
SignalWork connects internal systems such as BrassRing, Workday and SAP, plus external data, into a single view of the workforce.
It weighs the cost of each option against the risk of losing human judgment, recommending the mix that produces the best result.
Enterprises can preview the impact of third-party AI agents, tracked on the same ledger with the same cost and governance controls as human roles.
SignalOS customers Infinite and VetJobs will be the first to use SignalWork.
"You're running a mix of people and AI agents against goals that used to be staffed by people alone," said Rajeev Ronanki, Founder and CEO of Signal Labs. "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."
"After seeing the prototype, we're eager to use SignalWork. We've already seen proof that SignalWork eases the work of grant compliance by 50% and increases our productivity to fulfill those grants, further optimizing our workforce management," said Jamie Dale, Sr. Director of Technology & Data Infrastructure at VetJobs.
SignalWork connects internal systems (e.g., BrassRing, Workday, SAP) and external data (e.g., news, weather, geopolitical events, government planning) into a single view of the workforce, then determines what work should be prioritized and which mix of human judgment and machine capacity should perform it. Rather than optimizing for maximum automation, it weighs the cost of each option against the risk of losing human judgment or oversight, and recommends the mix that produces the best result.
Enterprises can preview the impact of third-party AI agents, tracked on the same ledger with the same cost and governance controls as human roles.
Decision Memory connects each allocation and action to its observed outcome. That evidence feeds back into the institutional world models, helping refine assumptions, assess where predictions differed from results, and improve future allocations as the organization changes.
"SignalWork is intended to move the focus from time-to-hire toward time-to-outcome by reading the funded work portfolio, identifying units of work called 'missions,' and connecting them with human and agentic AI capacity in a unified ledger," said 451 Research by S&P Global Senior Research Analyst, Ethan Ray.
Rehearse workforce choices. Use institutional world models to simulate alternative allocations and assess expected costs, dependencies, and risks before committing resources.
Allocate work and attention. Prioritize work across people and AI agents, and surface decisions that require human judgment.
Execute within enterprise controls. Act on approved allocations within defined permissions, budgets, and oversight requirements.
Source AI agents. Plan and provision third-party agents from SignalWork's marketplace directly to workforce plans.
Manage spending against outcomes. Monitor consumption and spending thresholds in the context of the work being performed.
Retain decisions and improve predictions. Maintain a traceable decision record and use observed outcomes to refine the models informing future choices.
"A plan built for a static headcount can't keep up with a workforce that changes shape every quarter: a new model ships, a team reorganizes, a division absorbs a layoff," said Ryan Jackson, Senior Director of Product at Signal Labs. "What you need isn't a planning tool that sits on the side. It's the system doing the allocating and the executing, updated as fast as the workforce itself changes."
About Signal Labs
Signal Labs builds Attention Infrastructure within a new category, Systems of Attention, helping companies across industries make more effective and defensible decisions by identifying which signals deserve attention, routing them to the right leaders in time to act, and capturing every decision in institutional memory. The company is backed by Lightspeed Venture Partners. In July 2026, Signal Labs acquired BrassRing, a cloud-based applicant tracking system with 25 years of Fortune 500 client results across 350 million applicants in 172 countries, extending Signal Labs' platform into workforce planning.
