Branded CV Parsing Automation

I need a small standalone application that can ingest raw candidate CVs (any common text-based or PDF source), automatically extract the usual résumé fields, and re-assemble them into a polished, on-brand Word document. The program must apply all of my recruitment agency’s visual identity—our logo in the header, our colour scheme throughout headings and accents, and our preferred font family—so every exported file looks consistent without any manual tweaking.

Functional outline
• Parsing: detect and map contact details, work history, education, skills and certifications with reliable text-mining logic.
• Formatting: drop the parsed data into one fixed, standardised template only (no need for multiple layouts) while honouring section order and spacing.
• Branding: inject logo, colour palette and font style exactly as supplied; these assets will be provided as SVG/PNG, HEX codes and font files.
• Output: generate a ready-to-send DOCX file. No PDF or HTML export is required.

Technical notes
The solution may be scripted (Python with python-docx, for example) or built as a lightweight desktop tool; I’m open to suggestions as long as it runs on Windows 10 without additional paid licences. Code should be clean, well-commented, and delivered with a quick setup guide so my internal team can maintain the template or colour codes in future.

Acceptance criteria
1. Feed a sample batch of five mixed-format CVs; receive five uniformly branded DOCX files in under two minutes.
2. Visual inspection shows precise logo placement, colour accuracy, and correct font usage.
3. Section headings, bullet lists and dates follow the supplied template exactly—no layout drift.
4. Source code and README compile/run error-free on a fresh Windows machine.

Please outline your preferred tech stack, estimated turnaround time, and any similar projects you’ve completed when you respond.