LegalTech startup
Legal Tech

Custom NLP model for legal analysis

Trained a specialized model to classify and extract data from legal documents

The situation

The startup needed to classify legal documents and pull key data at scale. General-purpose LLMs were expensive to run and hard to control, and manual review couldn't keep up with volume.

What we did

We fine-tuned a specialized model with PyTorch, Transformers, and LoRA, trained on legal data and served through FastAPI. The result is a compact, task-specific model that classifies documents and extracts structured fields reliably.

The outcome

The model reaches 96% classification accuracy, processes documents 50× faster than manual review, and is 10× smaller than general-purpose LLMs — making it cheap and predictable to run.

Key results

96% classification accuracy
50× faster than manual review
10× smaller than general-purpose LLMs

Technologies

PyTorchTransformersLoRAPythonFastAPIHugging Face

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