Underwrite · PCT-002 · Published note
Covenants out of the agreement
An associate on a new deal needs the covenant package, EBITDA add-backs, and key baskets from a publicly filed credit agreement before the term-sheet call.
Worked example: The Viavi term loan has no financial maintenance covenant at all (Article VI runs §6.01 to §6.09), and restricted payments are unlimited at pro forma Total Leverage of 3.50x or less. See the walk-through ↓
Today vs automated
- Read the whole agreementAssociate · manual
- Retype test levelsAssociate · manual, re-keying
- Hunt for definitionsVP / counsel · manual
- Email / meeting hand-offAssociate → VP / counsel
- A draft or final credit agreement lands in the data roomTrigger: starts on its own
- Read the agreementAutomated · Document parser
- Table every covenantAutomated · LLM
- Cite each sectionAI draft, human review · Model template
- Verify every cite against the agreementApprove / override · VP / counsel
AutomatedAI draft, human reviewHuman onlyTools: Data room, Document parser, LLM, Model template
Estimated valueestimate
160–1,320 analyst hours a year
$24k–$330k of time, vs an assumed $20k–$100k tool cost
Net: −$76k to $310k a year net of tool cost; at the low end of the assumptions it does not cover the tool cost.
Assumptions
- 6–12 analyst hours per agreement today; 1–2 hours with an agent, including review
- 40–120 agreements a year for one team
- $150–250 per hour loaded cost
- Tool or build cost $20,000–100,000 a year (both)
Estimate, based on the assumptions shown; your numbers will differ. How we estimate
What else it can do for the team
- Build the reporting and test-date calendar from the same read
- Load test levels and definitions into the monitoring template
- Compare the draft against the term sheet and list every mismatch
- Flag LME blockers and their gaps in the same pass
- Produce a one-page term summary for the IC pack
Worked walk-throughKey catch: The Viavi term loan has no financial maintenance covenant at all (Article VI runs §6.01 to §6.09), and restricted payments are unlimited at pro forma Total Leverage of 3.50x or less.
1. The input
A public credit agreement: the Term Loan Credit Agreement dated as of October 16, 2025, filed by Viavi Solutions Inc. as EX-10.1 to its 10-Q on 2025-10-30, with Wells Fargo Bank, National Association as agent. Source: SEC EDGAR exhibit. A public-company agreement is used because private-deal agreements are not public; the structure is the same.
2. What the AI produces
| Item | Finding | Section |
|---|---|---|
| Financial maintenance covenant | None found. Article VI runs §6.01 to §6.09 with no financial covenant section (covenant-lite term loan). | Art. VI (§6.01–6.09) |
| General debt basket | Greater of $122,500,000 and 50% of LTM Consolidated EBITDA | §6.01(a)(xiv) |
| General RP basket | Greater of $61,500,000 and 25% of LTM Consolidated EBITDA, plus Available Amount and Available Equity Amount | §6.08(a)(viii) |
| Ratio RP basket | Unlimited if pro forma Total Leverage Ratio ≤ 3.50x and no Event of Default | §6.08(a)(xiv) |
| Run-rate cap on (b)(ii) | (b)(ii) savings from later Specified Transactions / restructurings: capped at 30% of Consolidated EBITDA per Test Period, calculated after the add-backs; Reg S-X-compliant adjustments sit outside the cap | §1.01 “Consolidated EBITDA” cl. (b), 2nd proviso |
| J.Crew blocker: designation | Present. A Restricted Subsidiary holding Material IP cannot be designated unrestricted | §5.15 (last sentence) |
| Chewy blocker (guarantor release) | Present. Ceasing to be wholly owned does not release a guarantor unless the equity went to a non-Affiliate for a bona fide business purpose | §9.15 (proviso) |
Every row was read against the filed text (regex + section tracking on the filed HTML; every row hand-read against the filed text on 2026-10-16). Full table: ca-scan-2025a.json.
3. What a person still checks
- Open each cited section and confirm the number and the “greater of” grower both match.
- Read the defined terms the basket depends on (here, LTM Consolidated EBITDA) before you trust any capacity figure.
- Check for baskets that can be reclassified or stacked, and whether amounts reload.
- Confirm no later amendment changed the clause (search the borrower’s later 8-Ks and 10-Qs).
4. Where it breaks
- A “None found” result is only as good as the search: a covenant can sit in a schedule or a separate document.
- Long definitions with nested provisos get summarized too neatly; the second proviso is where caps hide.
- Scanned or image-only exhibits defeat text extraction.
How you get thereFour steps from prompting to an agentic workflow; most teams start at step 1.
Needs: an approved AI tool, a confidentiality policy.
Risk: unchecked answers, data pasted outside policy.
Typical starting point
Needs: field definitions, a template, document parsing.
Risk: breaks silently when formats change.
Needs: inbox/doc-store access, system write-back, logging.
Risk: acting on a misread; needs review gates.
The automated lane above
Needs: shared data model, permissions, audit trail, exception queue.
Risk: errors compound across steps; needs monitoring.
Solution optionsBuy (15 vendors listed), build or hybrid, with the trade-offs of each.
Hebbia, Rogo, AlphaSense, V7 Go, Orion (Private Credit AI), 9fin, Octus, Indus Valley Partners (IVP for Credit), Blueflame AI, Alphastream, CovenantIQ, CredCore, WhaleBlue, CreditBase, Raven (RavenRisk AI)
Fastest start; you adapt to the product's data model and pricing.
An LLM API, a document parser, a vector or document store, your data warehouse, and a review queue.
Fits your definitions exactly; you own maintenance and controls.
Vendor extraction feeding your own checks, templates and systems.
Common middle path; two things to integrate and govern.
Listing is not endorsement.
What changes for the team6–12 h → 1–2 h per agreement (estimate); coverage goes from the sections someone had time to read to every clause and schedule checked against the term sheet.
How it works
Full title: Covenants, baskets and add-backs out of a 200-page credit agreement, every line cited to a section
“200 pages in, one table out, every line cited to a section.”
Scenario
Public: an associate on a new deal needs the covenant package, EBITDA add-backs, and key baskets from a publicly filed credit agreement before the term-sheet call.
What the human still decides
Verify every cite against the agreement. Check definitions and step-downs yourself; models miss cross-references and amendments.
Why it matters
Add-back caps, cov-lite springing tests, and LME blockers are the 2026 documentation fight. Many vendors sell this.
Before and after
Before
- Read a 100–200+ page agreement (illustrative length)
- Find each financial maintenance covenant and its definitions
- Key covenants, levels and cure rights into a term-sheet grid
After (agent first draft)
- Agent reads the agreement (HTML or PDF)
- Outputs a table: covenant, test level, test frequency, definitions referenced, equity cure, section cite
- Quotes key definitions verbatim and says 'not found' when unsure
Agent pattern: extract → table → cite section → human check
Tools
- LLM with PDF/HTML input
- EDGAR full-text search for credit agreement exhibits (EX-10)
Try it: prompt and data
From this credit agreement, list every financial maintenance covenant with level, test date, and section number. Quote the definition of Consolidated EBITDA add-backs verbatim. If unsure, say 'not found'.
Data
Use only agreements that are publicly filed (many are exhibits to 8-K, 10-Q or 10-K filings). Never paste a confidential agreement into a consumer AI tool.
Who uses it, vendors and build
- Segments
- Direct lending, Special sits / distressed
- Who uses it
- Associate / VP (deal team), Special sits analyst
- Build
- Vendor + in-house
- In-house
- LLM + document parser + an eval set of 20 EDGAR agreements. Estimate: 2–4 weeks for a small team.
- Last verified
- 2026-10-15
Vendors that claim this capability
- Alphastream: covenant-basket-extraction, covenant-benchmarking
- Octus: covenant-benchmarking, document-summary
- CreditBase: covenant-benchmarking
- 9fin: covenant-basket-extraction, document-summary
- Blueflame AI: document-summary, covenant-basket-extraction
- 10 more vendors claim related capabilities. See all vendors for this stage →
Tags reflect each vendor's own public claims at the linked page (checked 2026-10-15). Not tested, ranked or endorsed.
Sources and related
- CredCore launches Credit Agents: legal, structural and financial agents that answer cross-discipline questions on a firm's own deal files
- Hebbia plugs Octus credit data in through the Octus MCP Connector
- Google releases Gemini 4 Argon, ranked #1 on the Vals Index for finance, legal and tax work
- Rogo adds Octus credit intelligence as a source inside Rogo agents
Part of the deal lifecycle: stage 4 of 7, Documents.
Next step
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Not investment advice. Names marked SAMPLE are fictional. Found an error? See the corrections log.