Saraswati Stitch®contact@saraswatistitch.com
Generic AI tools are a poor fit for finance, where the data is sensitive, the rules are specific, and every output has to be explainable. A custom model built on your own data and constraints, for reading documents or flagging anomalies, delivers where off-the-shelf cannot, as long as it stays auditable and a human owns every decision that counts.
Off-the-shelf tools miss your specifics
Your document formats, your rules, and your definitions of normal are particular, and a generic tool trained on someone else’s data misreads them.
Document work is manual and slow
Extracting structured data from invoices, statements, and reports by hand is a huge, repetitive cost and a source of error.
Anomalies hide in the volume
The one transaction that matters is buried in thousands, and a human reviewing them all is neither fast nor reliable.
How it works
- Define the decision and the rules. We start from what you need, reliable extraction or anomaly flags, and the rules and definitions that are specific to your finance operation.
- Build on your data. A model is trained and validated on your own documents and history, so it reads your formats and knows your normal rather than a generic one.
- Keep it explainable and auditable. Every extraction and flag comes with its basis, so a reviewer can check it and the output stands up to audit.
- Keep the human in control. The model extracts and flags; a person reviews and decides. It never moves money or finalises a number on its own.
Tools we reach for
- your documents and history as training data
- a model fit to the task (extraction / anomaly detection)
- an explainability + audit layer
- a human review-and-approve step
What changes
A model that reads your documents and flags your anomalies accurately because it was built on your data, saving hours of manual work while staying explainable, auditable, and firmly under human control.