OpenKnowra grids run whole enterprise functions on real-time context, governed. This is the Work and Workforce Engineering grid.
Demand, skills, supply and market signal resolved into live context, with an agentic operating system that redesigns work, forecasts demand, realigns talent and orchestrates human and AI execution, at scale.
Every function keeps its own view of the workforce, and each one disagrees. Demand is discovered late, supply is guessed, and reskilling runs off a catalogue no one connected to the plan. The cost shows up as staffing lag, over-hiring, and a wage bill nobody can trace to the work.
HR holds the plan of record, but it is rebuilt by hand each cycle and frozen the moment it ships. By the time the business moves, the plan already describes a workforce that no longer exists.
Finance funds positions against a different model, on a different calendar. The funded number and the planned number drift apart, and no one can say which roles the money is actually paying for.
The RMO tracks availability in spreadsheets updated after the fact. Bench supply is stale, so internal talent that could fill a gap stays invisible while a new requisition opens next door.
Talent acquisition sources against demand it cannot see far enough ahead, and hires externally for skills the org already has internally, because the two views were never joined.
Learning pushes generic curriculum disconnected from where demand is heading. Completion looks healthy while the skills that actually close the gap go unbuilt.
External skill supply, compensation and competitor hiring move faster than any internal model. Plans that ignore the market age within weeks, and you find out only when a search stalls.
Work and Workforce Engineering combines two capabilities into one context spine. The first understands your workforce: demand, roles, skills, supply and market signal resolved into one live model. The second acts on it: it forecasts, plans, fulfils, reskills and realigns talent, autonomously and governed.
Open roles, projects and attrition, a live role and skill architecture, employee proficiency and availability, and the external talent market resolved into one workforce model, with provenance on every signal. Not five systems disagreeing, a live picture connected to where the work actually is.
WWE clusters, digital workers and AI agents act on that context to forecast demand, plan supply, fulfil internally first, reskill and realign talent, with humans in command on external hiring, sensitive mobility and restructuring.
WWE is not an HRIS, an ATS, a planning spreadsheet or an LMS. Those store or move parts of the workforce. WWE understands the whole workforce and runs the decisions across it, at the moment the business changes.
This is what separates a grid from a solution. Work and workforce engineering opens into clusters, each cluster into running assemblies, each assembly composed of the workers, agents and APIs that do the work.
Ten operating areas. Every part of the workforce function has a home on the twin.
Complete functions that run end to end, governed at every step.
Workers own the role, agents reason and decide, APIs feed real-time context.
Every workforce decision moves through the same ordered, causal checkpoints, so the decision and its full trace are produced together, down to the source policy.
Every staffing, mobility and planning decision follows your policy and rules in order, not a probabilistic guess. A resourcing lead, HRBP or auditor can open the chain and see exactly why a person was matched, moved or hired, down to the source rule.
People stay in command on the high-stakes calls: external hiring, sensitive mobility, restructuring and anything that carries legal or people exposure.
The same reasoning substrate is formalized in peer-reviewed research for aerospace competency management and runs tier-one banking operations.
Certified to SOC 2 and ISO 27001, with an independent bias audit, and built for the transparency that regimes such as the EU AI Act now require.
On your roles, your skills, your supply, as the use case. Not a generic demo.