NextBill AI Invoicing Validation Workspace

Production execution workspace tracking computational inference, structural data shifts, and unified token audit trails live.

Manual Invoice Text Sandbox

Pass raw invoice records concurrently to see output label alignment across parallel engine weights.

v1_T (DistilBERT Core)

Primary Production Engine

Awaiting input execution...

v1_NB (Naive Bayes)

Statistical Word Probability Baseline

Awaiting input execution...

v1_L (Logistic Reg)

TF-IDF Structural Baseline

Awaiting input execution...

Dynamic CSV Evaluation Dashboard

Drop an evaluation file (`.csv`) containing an input text column. The platform computes real-time accuracy ratings, puts the winning model on top, and delivers an engineering explanation.

Comprehensive Cross-Dataset Benchmark Stories

An exact cross-examination of how varying language profiles (synthetic clean vs. messy real-world) change model behavior and trigger structural collapses.

📈 Scenario 1: Clean Synthetic Boundaries (faker_benchmark_v1.csv)

Training Corpus Core: data.csv (Synthetic template parameters)

Model Pipeline IdentifierAccuracyPrecision (Macro)Recall (Macro)F1-Score (Macro)
v1_T (Transformer Core)............
v1_NB (Naive Bayes)............
v1_L (Logistic Regression)............

Behavioral Summary: Traditional bag-of-words counting scripts function cleanly here because there is zero keyword context contamination across target categories.

📉 Scenario 2: Unstructured Real-World Dataset Shift (kaggle_test_data.csv)

Training Corpus Core: data.csv (Maintained identically to isolate drift factors)

Model Pipeline IdentifierAccuracyPrecision (Macro)Recall (Macro)F1-Score (Macro)
v1_T (Transformer Core)............
v1_NB (Naive Bayes)............
v1_L (Logistic Regression)............

Why Did the Traditional Models Completely Collapse? Traditional baselines completely collapsed into systemic single-class biases (v1_L guessed everything as Travel; v1_NB guessed Cloud/Software). The Transformer model maintained an accurate floor because its multi-head self-attention analyzes structural sentence context rather than matching isolated key terms.

On-Demand Background Fine-Tuning Console

Submit custom transaction logs (`.csv` files with explicit `text` and `category` headers) to start a background optimization task without blocking API availability.

Live System Audit Trail & Grouped Transaction Logs

Every transaction evaluated is preserved directly inside your server environment. Batch runs appear as a single summary row; expand them to view the individual item records:

Actions Timestamp Source Type Extracted Raw Text Payload / Meta v1_L v1_NB v1_T Core
Click sync to stream real-time logs from the storage system file layer...