Document AI · Analytics · 2024
Invoice Extraction & Analytics Dashboard — messy invoices to clean data
An end-to-end pipeline that turns unstructured invoices into validated, structured data with an analytics dashboard on top — cutting manual processing time ~80%.
By the numbers
~80%
less manual processing time
9+
validation criteria before data is trusted
End-to-end
upload → extract → validate → analyse
What it does
Invoices arrive in every shape imaginable. This pipeline ingests them, extracts the fields that matter, validates the extraction against 9+ criteria, and surfaces the results in a Streamlit dashboard for analysis — replacing a slow, error-prone manual step.
How it’s built
- Extraction — GPT-4 pulls structured fields from unstructured invoice input.
- Validation — before anything is trusted, it passes a set of 9+ checks (totals, required fields, format sanity). Failed extractions are flagged, not silently accepted.
- Analytics — a dashboard turns the cleaned data into something a person can actually reason about.
The outcome
Around 80% less manual time on the processing step, with validation doing the work of catching the cases the model got wrong — so speed doesn’t come at the cost of trust.
The dashboard is the visible part. The validation layer is the part that makes it safe to use.