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Upload README.md with huggingface_hub

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- ---
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- title: Finance Analyst Concept
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- emoji: 🦀
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- colorFrom: indigo
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- sdk: static
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- pinned: false
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- ---
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-
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ title: Finance Analyst (Concept)
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+ emoji: 💰
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+ colorFrom: green
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+ colorTo: gray
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+ pinned: false
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+ license: other
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+ ---
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+
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+ # Finance Analyst — Document Review Platform (Working manager + concept analytics)
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+
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+ A browser app that pairs a **functional financial-document manager** with a
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+ **concept analytics/AI layer** for monthly financial review.
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+
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+ > **Live demo:** https://finance-analyst-concept.vercel.app
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+ >
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+ > ⚠️ **Honest scope:** the document-management side is **genuinely functional**; the
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+ > analytics/AI side is a **concept** (illustrative figures). See below.
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+
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+ ## What actually works today
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+
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+ A real, self-contained client-side document manager:
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+
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+ - **Upload** financial documents (PDF / XLSX / CSV / images) by click or drag-drop.
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+ - **Persist** them in the browser via **IndexedDB** — the actual file bytes are stored
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+ and survive a refresh.
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+ - **Organize** by period/month, with per-month counts and storage totals.
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+ - **Download** or delete any stored file; clear a month or everything.
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+ - A stats bar (active periods, total files, storage used, last upload) computed from
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+ the real stored files.
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+
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+ ## What is a concept (not yet wired up)
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+
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+ - The **KPIs, charts, "AI-generated findings", and extracted line items** are
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+ illustrative sample data, not computed from your uploads.
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+ - The **"AI analyst crew"** is a visual workflow demo; there is no LLM call yet, and
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+ uploaded files are **stored but not yet parsed**.
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+
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+ ## What would make the analytics real (roadmap)
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+
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+ - Parse uploads client-side — SheetJS (`xlsx`) for Excel/CSV and pdf.js (+ OCR for
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+ scans) to extract tables/text.
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+ - A normalization layer mapping parsed rows to accounts/categories.
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+ - Compute the metrics (revenue, expenses, margin, cash flow, variances) from the
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+ parsed data and drive the KPIs/charts/table from it.
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+ - For genuine AI findings: a backend proxy calling an LLM (e.g. Anthropic Claude) on
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+ the extracted data, so no key is exposed client-side.
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+ - Real report export (PDF/XLSX) instead of the placeholder action.
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+
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+ ## Tech
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+
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+ Single self-contained HTML file. Vanilla JS, Chart.js, IndexedDB. No build step.
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+ Deploys as-is to any static host (Vercel, Netlify, GitHub Pages).
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+
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+ ## Privacy
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+
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+ No API keys, no backend, no data leaves your browser — uploaded files live only in
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+ your browser's IndexedDB.
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+
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+ ## License
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+
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+ See [LICENSE](LICENSE). Provided for review and evaluation.