Three programs, one operating model.
Each program targets a specific, well-documented gap in the education-to-employment pipeline. All three share the same architecture: open-weight foundation models, retrieval over authoritative public data, deployment through trusted institutional partners, and outputs released under permissive open-source licenses.
Career Navigator
An open-source, multilingual career navigation copilot for adult learners.
Audience
Adult learners at community colleges, American Job Centers, and refugee resettlement agencies.
Status
Design phase. Launching first pilot Q4 2026 with two partner institutions.
How it works
A Llama-based assistant deployed inside community college advising offices, workforce boards, and immigrant-serving CBOs. It translates a learner's existing skills, prior credentials, and language into a clear set of next steps: realistic local job openings, the skills gap to close them, and the shortest credential path to bridge it.
Technology approach
Open-source large language models (Meta Llama family), retrieval over public labor-market data (BLS, O*NET, public job postings), and on-device or low-cost cloud inference so partners with limited IT budgets can run it.
Research data backbone: AI4Good has in-kind access to Canaria's research-grade US labor-market dataset (900M+ deduplicated job postings, 82 enriched fields, SOC and 37,000+ skills taxonomy). See partnerships.
Skills Translator
A free tool that turns a resume in any language into a US-employer-readable skills profile.
Audience
Immigrants and refugees with international credentials; adult learners returning after caregiving; veterans translating MOS codes to civilian work.
Status
Research brief in development. Open call for institutional pilot partners.
How it works
For internationally trained professionals, refugees, and adult learners returning to the workforce. We ingest a resume, transcript, or oral history in the learner's first language and produce a US-standard skills profile aligned to the Department of Labor's O*NET and SOC taxonomies, plus a personalized list of credential-recognition pathways.
Technology approach
Llama multilingual models for translation and skill extraction; published government taxonomies for the target schema. Outputs are open data, reusable by any workforce program.
Research data backbone: AI4Good has in-kind access to Canaria's research-grade US labor-market dataset (900M+ deduplicated job postings, 82 enriched fields, SOC and 37,000+ skills taxonomy). See partnerships.
Educator AI Toolkit
Curriculum and classroom-ready prompts that help instructors at Title I schools and minority-serving institutions teach with, not around, AI.
Audience
Instructors and instructional designers at Title I high schools, community colleges, HBCUs, HSIs, and TCUs.
Status
First curriculum module in drafting. Seeking 10 founding teacher fellows for 2026 cohort.
How it works
A free, openly licensed (CC-BY) curriculum bundle for instructors at Title I high schools, community colleges, and minority-serving institutions. Includes a lesson library, model-agnostic prompt patterns built on Llama and other open models, and a teacher fellowship community of practice.
Technology approach
Reference implementations on Meta Llama 3 (8B and 70B) and other open-weight models so districts without enterprise budgets can run pilots locally.
Want a program in your community?
We are recruiting our first pilot cohort. Six months, no cost to your institution, third-party evaluation report included. Community colleges, workforce boards, refugee resettlement agencies, Title I schools, and minority-serving institutions are eligible.