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README.md
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---
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<!--
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SimplyFI β’ Organization Card (Hugging Face)
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Usage: put this README.md inside a Space named `README` under your org.
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Assets to add in the same Space repo:
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/assets/simplyfi-banner.png
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/assets/simplyfi-logo.png
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Replace bracketed placeholders like [link] / [email].
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-->
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<p align="center">
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<img src="./assets/simplyfi-banner.png" alt="SimplyFI β AI Agents for Banking" width="100%" />
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</p>
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<h1 align="center">SimplyFI β AI Agents for Banking</h1>
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<p align="center">
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Intelligent automation for <b>Customer Engagement</b>, <b>Compliance</b>, <b>Lending</b>, and <b>Trade Finance</b>.<br/>
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Models, datasets, and Spaces for document understanding, risk, and decisioning β production-first and audit-ready.
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</p>
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<p align="center">
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<a href="[website]"><img alt="Website" src="https://img.shields.io/badge/Website-SimplyFI-blue.svg"></a>
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<a href="[linkedin]"><img alt="LinkedIn" src="https://img.shields.io/badge/LinkedIn-@SimplyFI-informational.svg"></a>
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<a href="mailto:[email]"><img alt="Contact" src="https://img.shields.io/badge/Contact-hello%40simplyfi.in-success.svg"></a>
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<img alt="Industry" src="https://img.shields.io/badge/Industry-Banking%20%26%20Financial%20Services-8A2BE2.svg">
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</p>
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---
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## What we publish
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- **Models**: OCR/IE, invoice understanding, entity linking (KYC/AML), credit signals, dialogue agents (RAG+RLHF).
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- **Datasets**: Synthetic & anonymized corpora for invoices, SWIFT/LC patterns, trade compliance, FAQs.
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- **Spaces**: Demo apps for **document triage**, **explainable decisions**, and **agentic workflows**.
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- **Notebooks**: End-to-end examples β from fine-tuning to human feedback (RLHF) and safe deployment.
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> Prefer **bank-grade** controls? We support **gated access**, **EULAs**, and **private org Spaces** for sensitive assets.
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---
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## Highlights
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- **SIMBA** β our production platform for **Trade Finance & Banking AI**: OCR β extraction β validation β decisioning
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- **Agentic Workflows** β multi-tool agents with grounded retrieval, guardrails, and human-in-the-loop review
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- **Compliance by design** β redaction, PII handling, lineage, prompt/trace logging, and model cards with usage guidance
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---
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## Explore
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### Featured models
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| Purpose | Model | Tasks | Notes |
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| Invoice Understanding | [`SimplyFI/invoice-extractor`](https://huggingface.co/SimplyFI/invoice-extractor) | token-classification, table-qa | line-item, taxes, totals, vendor |
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| Trade Compliance NER | [`SimplyFI/trade-ner-compliance`](https://huggingface.co/SimplyFI/trade-ner-compliance) | token-classification | sanctions terms, ports, HS codes |
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| Banking Assistant (SFT) | [`SimplyFI/banking-assistant-sft`](https://huggingface.co/SimplyFI/banking-assistant-sft) | text-generation | safe, concise answers with citations |
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| Risk Signals | [`SimplyFI/risk-signal-classifier`](https://huggingface.co/SimplyFI/risk-signal-classifier) | sequence-classification | escalations & review routing |
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> Replace links above with your actual repos (or keep as placeholders until published).
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### Example: quick inference
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```python
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from transformers import AutoModelForTokenClassification, AutoTokenizer, pipeline
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repo = "SimplyFI/invoice-extractor" # update if different
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tok = AutoTokenizer.from_pretrained(repo)
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mdl = AutoModelForTokenClassification.from_pretrained(repo)
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ner = pipeline("token-classification", model=mdl, tokenizer=tok, aggregation_strategy="simple")
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text = "Invoice 9081 from Alpha Plastics Pvt Ltd, Total βΉ1,24,560 due on 2025-11-15"
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print(ner(text))
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