Workforce infrastructure, now AI-powered.
Turn training budgets into verified employment. Governments spend billions on workforce programs and measure the wrong thing: enrollments instead of employment. WIL has a five-phase framework that produced an 82% interview rate, 50% placement in four months, and an 8.03x ten-year ROI across 5 cohorts and 790 participants in Canada. It is open source and ready to replicate.
Training budgets don't reach jobs.
Public workforce programs measure enrollments and hours. They rarely measure employment, and when they do, the data arrives 12 to 18 months late. By the time a funder can answer 'did this produce jobs', the cohort is long over and the money is spent.
Late data
Employment outcomes get measured 6 to 18 months after the fact. Too late to course-correct a live cohort.
Fragmented delivery
Training, mentorship, and hiring sit in different systems that don't share data.
2 to 5 percent interview baseline
Without AI-assisted job search, most applicants get filtered out of interview queues before a human reads their resume.
No line of sight to ROI
Agencies can't connect dollars spent to jobs, tax revenue, or lifetime earnings.
A proven five-phase framework.
WIL built and ran a framework that handles the whole pipeline: intake, cohort training, mentorship with work-integrated learning, AI-powered job preparation, and verified placement. It is open source. Governments and training organisations can deploy the whole framework or drop in individual phases.
- 82% interview rate with AI tools (16 to 40 times the industry baseline)
- 50% job placement within four months (DTTP 1.0)
- 192 jobs tracked within 12 months (DTTP 2.0, verification ongoing)
- 8.03x government ROI over 10 years
- $3,559 cost per completion and $4,095 cost per work placement
Four modular components.
Deploy the full framework or start with one component. Each one runs independently and plugs into existing agency systems.
AI Talent Navigator
An agentic system that matches residents to the right training pathway, then to real openings at partner employers. Runs continuously, at population scale.
Framework deployment
End-to-end deployment of the five-phase Training-to-Outcome Framework. We bring the operating model and the playbooks.
AI Job Preparation Toolkit
Resume, cover letter, interview practice, and application matching. The same stack that produced the 82% interview rate.
Outcomes dashboard
Live visibility into enrollment, completion, interview, and placement. Cost per outcome and ROI built in.
Evidence, not promises.
Every number here is sourced in the 2025 WIL Impact Report. The framework itself is published under an open licence.
So no opportunity is out of reach.
WIL's framework fits the Economy stream of Google.org's AI for Government Innovation initiative: using AI to help public agencies deliver measurable employment outcomes. We are looking for government and philanthropic partners to run the framework in new jurisdictions.
Backed by Canadian innovation funders.
WIL's work is funded by Canadian innovation funders and co-delivered with training partners and a network of 87 employers who hire our graduates.
Read the evidence.
5 cohorts. 790 participants. One framework. Full impact report and methodology are public.