Contract and credit-document review on Amazon Bedrock
How a bank could extract key terms from loan agreements and covenants with Textract and Bedrock — with analysts confirming every result.
The situation
A commercial lending team manually reads loan agreements, amendments and covenant certificates to capture key terms and deadlines. The work is slow, error-prone and peaks at quarter end.
Our approach
Define the data model
Agree the terms to capture — parties, amounts, rates, covenants, dates — and how each is validated.
Extract text reliably
Use Amazon Textract to extract text, tables and layout from scanned and digital documents.
Interpret with a model
A Bedrock model identifies and normalises the agreed terms, quoting the source clause for each.
Analyst verification
Analysts review extracted terms side by side with highlighted source text and approve or correct them.
Load and monitor
Approved data flows to the loan system; covenant deadlines trigger reminders.
Typical technology
What success looks like
Metrics we would agree with you up front and track throughout:
- Review time per agreement
- Extraction accuracy on a labelled test set
- Share of fields accepted without correction
- Missed covenant deadlines
- Quarter-end backlog
This is an illustrative scenario showing how Inspired Infotech approaches this type of problem. It does not describe a specific client, and actual approach and outcomes depend on each organisation’s systems, data and goals.
Services behind this scenario
Amazon Bedrock Services
Generative AI and agents on Amazon Bedrock — RAG, guardrails and model choice inside your AWS account.
Learn moreGenerative AI
LLM-powered assistants, RAG search and content automation — secure, grounded and enterprise-ready.
Learn moreAI & Machine Learning
Predictive models, computer vision and NLP built on your data and taken all the way to production.
Learn moreFacing a similar challenge?
Let’s talk about your situation and what a realistic plan looks like.