docs/PRODUCTION_READINESS.md

FinEE Production Readiness Report

Current Status vs Production Target

Aspect	Current Status	Target	Gap
Training Data	137,267 samples	50,000+	✅ EXCEEDED
Bank Coverage	8 banks	15+ banks	⚠️ Need 7 more
Document Types	Email, SMS	Email, PDF, SMS, Images	⚠️ PDF/Image parsers added
Evaluation	F1=56.8% (regex)	F1 > 95%	❌ LLM fine-tuning needed
Deployment	Mac (MLX)	Cloud + Mobile + Edge	⚠️ Export scripts ready
Users	0 external	10+ active	❌ Beta testing needed

Benchmark Results

Regex Extractor (Baseline)

Field	Accuracy	Status
Amount	85.8%	✅ Good
Type	65.0%	⚠️ Needs improvement
Bank	100%	✅ Excellent
Merchant	28.3%	❌ LLM needed
Category	15.8%	❌ LLM needed
Overall	56.8%	❌ Below target

Expected with LLM Fine-tuning

Field	With LLM	Target
Amount	~98%	99%
Type	~97%	98%
Bank	100%	100%
Merchant	~92%	95%
Category	~88%	90%
Overall	~95%	95%

Priority Actions

High Priority (This Week)

1. Fine-tune LLM on 137K dataset

   • Use scripts/finetune.py with MLX or PyTorch
   • Target: Phi-3 or Llama 3.1 8B
   • Expected improvement: +40% F1

2. Add remaining banks

   • BOB, Canara, Union, IDBI, Federal, South Indian, Karur Vysya
   • Update scripts/data_pipeline/generate_synthetic.py

3. Test PDF parsing

   • Collect sample bank statements
   • Test with src/finee/pdf_parser.py

Medium Priority (This Month)

4. Export to ONNX

   • Run scripts/export_model.py --format onnx
   • Test inference speed

5. Deploy to HF Inference

   • Push model to Hugging Face
   • Enable Inference API

6. Get beta users

   • Share demo: https://huggingface.co/spaces/Ranjit0034/finee-demo
   • Collect feedback

Low Priority (Next Month)

7. Mobile deployment (GGUF)
8. Multi-turn agent
9. Knowledge graph integration

Files Added

File	Description
src/finee/rag.py	RAG engine with 50+ merchants
src/finee/api.py	FastAPI backend (8 endpoints)
src/finee/ui.py	Gradio web interface
src/finee/pdf_parser.py	PDF/Image parsing
scripts/benchmark.py	Production benchmark suite
scripts/export_model.py	ONNX/GGUF/CoreML export
tests/test_rag.py	33 comprehensive tests

Commands

# Run benchmark
python scripts/benchmark.py --test-file data/instruction/test.jsonl --max-samples 1000

# Fine-tune LLM
python scripts/finetune.py --backend mlx --model microsoft/phi-3-mini-4k-instruct

# Export to ONNX
python scripts/export_model.py models/finetuned --format onnx

# Start API server
python -m finee.api --port 8000

# Launch Gradio UI
python -m finee.ui --port 7860

Links

• Demo: https://huggingface.co/spaces/Ranjit0034/finee-demo
• Dataset: https://huggingface.co/datasets/Ranjit0034/finee-dataset
• Model: https://huggingface.co/Ranjit0034/finee-phi3-4b
• Code: https://huggingface.co/Ranjit0034/finance-entity-extractor

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Last updated: 2026-01-14