Why local AI?
Your CV is processed by a small model running on your device. Its extracted text and drafts are not sent to an AI provider or this site's server.
Local TCV
Drafting Tri-Agency Thematic CV (TCV) using local AI
Turn a conventional CV into evidence for a Canadian Tri-Agency narrative CV. The assistant helps you find your role, relevance, quality, impact, and mentorship evidence before it drafts. You remain the author and fact-checker.
Your CV is processed by a small model running on your device. Its extracted text and drafts are not sent to an AI provider or this site's server.
Local models are slower and less capable than leading cloud models, require a large first download, and may miss context. In this tool, all data stays on your local machine and is not sent to the cloud.
Agency-informed prompts, application-specific selection, evidence-gap checks, and anti-invention rules help you find the right material—not merely rewrite a publication list.
All three routes lead to the same evidence review. Choose the source that gives you the best factual starting point.
Local processing avoids sending sensitive CV content to a cloud model, but it moves the computing work to your device. The first visit downloads the model into browser storage; later visits can usually reuse the cached copy.
This will download approximately 2.2 GB of AI model files. Use Wi‑Fi and keep this tab open until loading finishes.
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Choose a text-based PDF, Word (.docx), or plain-text file. Scanned image PDFs are not supported in this version.
Try: “For the [opportunity], the project will address [problem] with/for [partners or users]. In my role as [role], I will be responsible for [specific responsibilities]. My prior [expertise or experience] is especially relevant to [criterion or project need].”
Review what the model found, then complete the evidence pathway from your contribution to its use and outcomes. Do not leave invented facts in place.
Choose your discipline so importance ranking and drafting use the right evidence signals. Confirm the top elements, then generate one section.
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