Credit Agreement Analysis
Semeris now analyses credit agreements, not just CLOs. Upload your own documents into a private workspace, and Semeris forms intelligent clusters from the data — so you can see lender exposure across the whole book and explore how it all connects as a mind-map, instead of reading agreement by agreement.
The problem with credit agreements at portfolio scale
Credit agreements are long, bespoke, and scattered across deals and counterparties. Any single agreement is manageable; the hard question is the one that spans the book — where is each lender exposed, on what terms, and how do those positions relate? Answering it manually means opening dozens of documents and holding the map in your head. Generic document tools extract text but don't build that picture.
What Semeris does for credit agreements
- Your own workspace. Upload your credit agreements into a private, permissioned library — your workspace — that only your team can see. Nothing is shared with other firms, and your documents never train a model.
- Intelligent clustering. Semeris forms clusters from the extracted data, grouping agreements and terms so patterns and concentrations surface on their own rather than being hunted for.
- Lender exposure at a glance. See which lenders are exposed where across the portfolio — by borrower, facility and terms — in one view instead of many.
- A mind-map view. Explore the relationships between lenders, borrowers and terms as a visual map, so the structure of the book is something you can see rather than reconstruct.
- Verified, traceable extraction. The same analyst-verified extraction and one-click source traceability behind Semeris's CLO analysis applies here — every datapoint links back to the exact language it came from. SOC 2 certified.
Who it's for
Private-credit lenders, CLO and loan-fund managers with direct-lending books, law firms, and investors who need to understand credit-agreement exposure across a portfolio — not just within a single deal.
See what your own credit agreements reveal — request a demo.
FAQ
What is the Semeris workspace for credit agreements? The workspace is your private, permissioned document library inside Semeris. You upload your own credit agreements, and Semeris analyses them for you and your team alone — sandboxed from other firms' data, with your documents never used to train a model. It's where your credit-agreement clusters, lender-exposure views and mind-maps live.
Can Semeris analyse my own uploaded credit agreements? Yes. Credit agreements are a supported asset class in Semeris. You upload your documents into your workspace and Semeris extracts and structures the terms — analyst-verified, with every datapoint traceable to its source passage — so you can compare terms and see exposure across your whole book, not just one agreement at a time.
How do I see lender exposure across a portfolio of credit agreements? Semeris forms clusters from the extracted credit-agreement data and presents lender exposure across the portfolio in a single view — showing which lenders are exposed to which borrowers, on what terms — so concentrations are visible without opening each document.
How does Semeris cluster credit agreement data? Semeris extracts structured data from your uploaded credit agreements and groups it into intelligent clusters, so related agreements, lenders and terms sit together and patterns emerge automatically — turning a pile of separate documents into a navigable map of the book.
Does Semeris offer a visual, mind-map view of lender exposure? Yes. Semeris presents the relationships between lenders, borrowers and terms as a mind-map-style visual, so you can explore how exposures connect across the portfolio visually rather than reconstructing them from individual documents.