AI credit analysis that shows how much debt could rank ahead of your bonds, by which clause, on which page
Every credit question answered in minutes, each sentence pinned to its tranche and page.
See one case, screen by screen ↓AI Credit Analysis is an AI credit analysis tool for buy-side credit teams: ask a credit question in plain words, and eight agents answer it from the documents that decide it — credit agreements as amended, indentures, intercreditors, filings in their original language, call transcripts and your own credit notes. Where research assistants from data vendors answer from their own content, this AI credit research reads your documents and stays inside your information barrier. Every sentence is cited to its page and pinned to the tranche it concerns on a capital structure built from the documents. The analyst decides what stands, and a senior analyst approves the credit memo before a portfolio manager reads it.
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In high yield credit research, whether new debt can be put ahead of a fund's bonds is decided in documents nobody reads end to end: a credit agreement of 250 to 500 pages and every amendment to it, two or more indentures, the intercreditor, the latest 10-Q and, sometimes, a foreign subsidiary's annual report in its own language. A buy-side credit analyst covering 30 to 80 issuers traces defined terms from “Incremental Cap” to “Consolidated EBITDA”, applies amendments in order and works out each “greater of” basket in a spreadsheet — while liability management exercises keep coming. That is credit agreement analysis done by hand, one issuer at a time.
The risk sits in what one document allows and another misses: a revolver maturity that springs ahead of the notes, a J.Crew blocker that does not reach the subsidiary holding the patents, a house note written after an amendment it missed. Research assistants from data vendors answer from their own content, not from the fund's indentures, notes or information barrier — and a credit memo that cannot show which page supports which sentence has no answer when an examiner asks.
Estimated split for one priming-capacity question on a sponsor-owned high-yield issuer, by hand and with the solution, including the analyst's and the senior analyst's review.
Eight agents read every agreement, indenture, filing and call, and pin each cited sentence to its tranche; the analyst decides and a senior analyst signs.
Friday, October 16, 09:14 ET. Ahead of Monday's investment committee, Meg Castellano, the high yield portfolio manager, asks whether Halvorsen Packaging can put new debt ahead of the 7.625% Senior Notes due 2029 that three Quillfield funds hold — $86.4 million in all. The house note of June 12 said secured capacity was under $150 million. Here is what happens next, screen by screen, in the working solution.
Nadia covers 54 issuers in packaging and paper, chemicals and building products, and Monday's investment committee has two of her names. Overnight the agents re-ran 12 watched questions: Amendment No. 4 raised Brennick Chemicals' restricted-payments basket, and Tessaro Building Products' ratio debt capacity fell from $160M to $41M after its 10-Q. Meg wants a priming view on Halvorsen before Monday, so Nadia asks in plain words.
“Can Halvorsen Packaging put new debt ahead of our 2029 unsecured notes?”
The Planner recognizes the issuer, finds the three holding funds and splits the question into four sub-questions across 9 documents: first-lien capacity under the credit agreement, what the 2029 indenture limits, whether value can move outside the guarantor group, and what management has said about the 2029s. Each names the agent and the documents it will use. Nadia can untick any of them or add her own.
“Nothing is read until you run it.”
The Wall agent checks Nadia's side of the information barrier first: 6 public sources searched, lender sites not searched. Then the readers work in parallel — the Indenture agent through the credit agreement (318 pages, conformed through Amendment No. 2), both indentures and the intercreditor; the Filings agent through the 10-Q and the Norwegian subsidiary's annual report; the Call agent through the Q2 2026 call transcript.
Wall agent: “Public side: 6 corpora searched · lender sites not searched.”
The answer arrives beside a capital structure analysis built from the documents — a ladder of non-guarantor debt, revolver, term loan B, secured notes, our notes and equity — with each sentence pinned to the tranche it concerns. Yes: the credit agreement allows incremental first-lien debt of the greater of $350 million and 57% of EBITDA with no ratio test, raised from $250 million by Amendment No. 2, plus about $128 million of ratio debt. The Citation Checker removed one sentence with no source and corrected one figure that had used EBITDA from a press release.
“8 of 8 sentences cited · 16 passages · 9 documents · 1 removed · 1 recalculated.”
Reading documents against each other, the Cross-reference agent links credit agreement §2.05(c) on page 57 to the 10-Q's long-term debt note: the revolver's June 2030 maturity springs to December 14, 2028 if more than $150 million of the 2029 notes remain, and the 10-Q shows all $600 million outstanding. It found 7 links — 4 confirmed, 2 to review — and one conflict: the June 12 house note put secured capacity under $150 million, though Amendment No. 2 had already raised the basket to $350 million on March 3.
Its limit: it proposes links; a person confirms or dismisses each one.
A second route sits outside the guarantor group. Page 47 of Halvorsen Emballasje AS's Årsrapport 2025 says, in Norwegian, that the company owns the group's barrier-film patents and technology and is not a guarantor of the group's loans and bonds. The credit agreement's IP blocker reaches only unrestricted subsidiaries, and the Norwegian company may borrow up to $153 million under the non-guarantor basket.
The Filings agent always shows the original beside the English; below 0.90 translation confidence, a person checks it first.
Sentence 7 scores 0.83, under the 0.85 threshold. The open point is one judgment: are the barrier-film patents “Material Intellectual Property”? The agent shows the definition and the annual report's figure — barrier film is 41% of group sales — and leaves the call to her. Nadia confirms it with the reason code “Confirmed against definition”.
“I, Nadia Farouk, make this decision; it is recorded with my name, the time, the reason and the evidence.”
Nadia pushes all eight sentences into credit memo M-26-0391, “Halvorsen Packaging — 2029 notes: priming capacity”, under Capital structure and covenant protection, every footnote kept. The push stays blocked until she acknowledges the conflict with the June 12 note, which put secured capacity under $150 million before Amendment No. 2 raised the basket. In all, about $631 million of new debt could rank ahead of our notes today, moving them from 3.85x–4.83x to 4.88x–5.86x of EBITDA. Her recommendation moves the 2029 notes to underweight in the High Yield Bond Fund and Global Credit Opportunities and holds them in Strategic Income, and she submits it for approval.
“You are the maker. Daniel Okafor approves before Meg Castellano can read it; you cannot approve your own memo.”
In Daniel's approval queue the memo is due before Monday's committee. The Citation Checker re-read all 8 sentences at 10:02 against the current document versions. Three are flagged — 2 was recalculated, 7 was decided by a person, 8 is computed — and Approve opens only when he has checked them. He approves with the reason code “Evidence verified”; Meg can now read the memo, and the June 12 note is marked superseded.
“Approve opens when the 3 flagged sentences are checked.”
Every question, plan, wall check, passage read, decision and approval is on the audit trail, for people and agents alike. Elena exports the pack for Q-26-10482 and memo M-26-0391: 23 events, 16 passages and 41 pages — each passage with its page image and document version — plus the sentence-to-source map, decisions with reason codes, the agent versions in force and who viewed the memo, as PDF for reading and JSON for systems.
“EP-26-0117 ready · 23 events · 16 passages · 41 pages · SHA-256 9f2c4e1a…b70d · logged.”
The same Halvorsen answer, seen by five of the people who carry it — what their week looked like, and what it looks like now.
Eight agents read every agreement, indenture, filing and call, and pin each cited sentence to its tranche; the analyst decides and a senior analyst signs.
Decides, per person and per fund, which sources may be searched — from the control room's wall list, the restricted list and fund entitlements — before anything is chosen, and records what was not searched on every answer.
Resolves the issuer and instrument, looks up holdings read-only, splits the question into sub-questions, picks the documents for each, shows the plan and waits.
Reads credit agreements as amended, indentures and intercreditors, traces defined terms across them and computes each basket at the EBITDA the agreement defines.
Reads 10-Ks, 10-Qs, 8-Ks and foreign annual reports in their original language, with page anchors.
Reads earnings-call and investor-day transcripts and quotes management exactly, by speaker.
Links what one document says to what another allows — a springing maturity, a blocker that misses a subsidiary — and flags conflicts with the house's own credit notes.
Re-reads every cited passage, recomputes every figure and removes any sentence it cannot cite, showing what it removed and what it recalculated.
Inserts the chosen sentences into a credit memo with their citations, routes it for approval and marks superseded house notes.
The analyst decides; a senior analyst approves the memo. The agents propose; a named person decides.
Under every answer, ask the agents a follow-up or tell them what to change. Every reply cites its passages, and the ladder redraws for a scenario.
What if EBITDA falls 15%?
At EBITDA of $520.2M the free-and-clear basket stays at its $350M floor, ratio debt drops to zero (4.00 × $520.2M is below the $2,320M already secured), and the Norwegian basket falls to its $150M floor: $500M could rank ahead of us, and our notes would sit at 5.49x–6.65x. I redrew the ladder for this case.
Which of my issuers have the same blocker gap?
Two more of your 54 issuers keep IP in a non-guarantor restricted subsidiary that their blocker does not reach: Merrow Specialty Polymers (blocker §6.09(k), IP in a Dutch subsidiary) and Ardent Closures (§7.06(l), IP in Ardent Closures Canada). Halvorsen is the third.
Why is sentence 7 below the threshold?
The Norwegian report says the company owns the barrier-film patents and is not a guarantor — that part is clear (0.96). The 0.83 is for one inference: that those patents are “Material Intellectual Property”. Barrier film is 41% of group sales, which points to yes, but materiality is a judgment the credit agreement leaves to the borrower, so I ask you.
Draft two lines for Meg
Draft: “Halvorsen can put about $631M ahead of our 2029 notes today — $478M of first-lien debt under its credit agreement and $153M at its Norwegian patent-holding subsidiary; the revolver springs to December 2028 unless the 2029s are refinanced.” It goes to Meg only after Daniel approves the memo.
13 screens from the working solution, on its sample data. Pick one to see it large.
The rules every answer is checked against are settings — versioned, on the audit trail, and changed only with a second signature.
| Setting | Default | Choose from |
|---|---|---|
| Sentence confidence threshold | 0.85 | Any value from 0.70 to 0.95 |
| Translation confidence | 0.90 | 0.85 · 0.90 · 0.95 |
| Arithmetic tolerance | 0.5% | 0.1% · 0.5% · 1.0% |
| Stale answer | 90 days or new document | 30 days or new document · 90 days or new document |
| No uncited sentence | Always on | Locked on |
| Plan before reading | Always on | Locked on |
| Conflict with a house note blocks a memo push | On | On · Off |
| Retention of questions, plans, passages, decisions, approvals and viewers | 7 years | 5 years · 7 years · 10 years |
Every figure is labelled: a target the solution is built to, an estimate, a typical published result, or a proven one.
“demo” = seen in the working solution, on its sample data · “target” = the design goal, measured in the live solution · “estimated” = our estimate · “typical” = published figures (American Banker, 2025 — 16 liability management exercises in Q1 2025 against 7 a year earlier; FA-Mag, 2025 — 32% of 158 high-yield bonds with a J.Crew blocker; White & Case — leveraged loan agreements from 205 pages in 2010 to 473 in 2020; analysts covering 30–80 issuers and credit agreements of 250–500 pages, from our division research; Investment Advisers Act Rule 204-2). People, firms, funds, issuers and securities named on this page are fictional — characters and sample data in the working solution.
AI Credit Analysis is an AI credit analysis tool for buy-side credit teams: ask a credit question in plain words, and eight agents answer it from the documents that decide it — credit agreements as amended, indentures, intercreditors, filings in their original language, call transcripts and your own credit notes. Where research assistants from data vendors answer from their own content, this AI credit research reads your documents and stays inside your information barrier. Every sentence is cited to its page and pinned to the tranche it concerns on a capital structure built from the documents. The analyst decides what stands, and a senior analyst approves the credit memo before a portfolio manager reads it.
Here, AI in credit analysis means the agents do the reading and the arithmetic, and people make the calls. A Planner splits the question and shows its plan; specialist agents read agreements, filings and calls; a Cross-reference agent reads documents against each other; and a Citation Checker recomputes every figure and removes anything it cannot cite. In the demo, a priming question is answered in 96 seconds, and one question asked across 54 issuers returns 51 answers in 6 min 40 s.
That is the question the demo answers. The agents compute each basket that could put debt ahead of a holding — free-and-clear incremental capacity, ratio debt, a non-guarantor subsidiary basket — check how much room your own indenture's debt and lien covenants leave, and state the result in dollars and turns of EBITDA. The figure counts new debt only; an undrawn revolver that is already committed is shown separately, with what it would add if fully drawn. They also flag routes that are easy to miss, such as a revolver maturity that springs ahead of your notes or an IP blocker that does not reach the subsidiary holding the patents.
The Indenture agent applies every amendment in order, traces defined terms such as “Incremental Cap” through the agreement and computes “greater of” baskets at the EBITDA the agreement defines. Each figure cites its clause and page, and the Citation Checker recomputes it within a 0.5% tolerance. Foreign filings are read in their original language and shown beside the English.
Yes. The Wall agent applies the control room's wall list, the restricted list and fund entitlements before the Planner chooses a single document, and every answer records what was not searched. Lender-site material such as compliance certificates is not searched for a public-side analyst; a wall crossing is requested with its restricted-list effect shown and decided by Research Compliance. Each wall check is on the audit trail under the firm's Section 204A information-barrier policy.
Every question, plan, wall check, passage read, decision, approval, setting change and export is on the audit trail with who, when, why and the evidence. Retention is a setting: the house policy in the demo keeps records 7 years, where the setting notes that Rule 204-2 asks for 5, and records under legal hold are never deleted. The evidence pack for any answer or memo exports as PDF and JSON, sealed with SHA-256.
No, and it is not built to. Using AI for credit analysis here does not move the decision: the agents never approve a memo or cross the wall. Sentences below the confidence threshold go to the analyst to confirm, edit or remove with a reason code; the author of a memo cannot approve it; a senior analyst checks the flagged sentences and signs; and changes to thresholds, roles or agent versions need a second signature.
The Agentic Solution Engine builds and deploys it from your requirements and documents — your credit agreements, indentures, credit notes and the systems that hold them — and it goes live once every quality gate has passed. Setup follows a checklist: connect the systems, choose what the agents may read, map funds and holdings, set the wall, roles and thresholds, and pass a golden-set test of questions with known answers.
Every basket in dollars and every leakage route found, before books close.
1-min demoProspectus ReviewEvery deal that fits a fund briefed and decided before books close, every line cited.
1-min demoInternal Credit RatingEvery rating cited to its page, and every two-notch split explained before committee.
1-min demoWe'll run AI Credit Analysis on a sample of your own credit agreements, indentures and credit notes.