Purpose-built vs. retrofitted: why private credit needs credit-native monitoring
Lumonic Team
Credit-Native Portfolio Monitoring vs Equity-First Platforms: why private credit needs credit-native monitoring
TLDR
Private credit monitoring runs on the loan lifecycle, where covenant testing is a legal obligation tested on a fixed cadence, not a quarterly mark like the IRR-driven workflows equity platforms were built around.
Chronograph and 73 Strings serve both equity and credit managers. Chronograph launched a private credit platform in June 2026, and 73 Strings positions itself around valuation, so buyers should ask each how covenant testing and certificate handling fit its data model.
The data model shows up in daily work: ask how each platform handles compliance certificates, borrowing base certificates, and covenant step-downs across amendments without a spreadsheet alongside it.
Lumonic is the system of record for credit and equity fund portfolios, with covenant tracking, compliance certificate ingestion, and source-cell traceability organized around the loan lifecycle.
The Wrong Data Model Is the Problem, Not the Feature Gap
A monitoring platform's data model decides what it does natively and what it can only approximate through workarounds. Before you compare feature lists, look at the endpoint each platform is built to reach. An equity-first tool organizes everything around a quarterly mark. A credit-native tool organizes everything around a loan that has obligations testing on a schedule the borrower controls.
These two endpoints pull a platform's architecture in opposite directions. A valuation engine treats data as inputs that resolve into a defensible number every 90 days, so versioning, point-in-time reproducibility, and IRR rollups become the hard problems worth solving. Credit monitoring runs on a different clock. A debt-to-EBITDA breach forces an enforcement decision within days, not at the next review cycle, and a missed compliance certificate starts cure periods running without your knowledge. The data model has to treat covenant obligations and delivery deadlines as first-class objects, not as fields attached to a valuation record.
Chronograph describes its architecture as a deterministic system of record with full versioning and point-in-time reproducibility for data. That is genuine engineering, built over a decade. For a credit team, the question to ask is how that architecture handles detecting a breach between reporting periods.
73 Strings organizes its platform into three products, 73 Extract, 73 Monitor and 73 Value, and positions itself as "the valuation technology moving private markets forward" (73 Strings). Buyers should ask how covenant testing fits alongside the valuation workflow.
Neither platform is weak at what it was designed for. Both now market private credit capabilities, so the useful test is whether covenant compliance, certificate ingestion, and borrowing base tracking sit at the center of the data model you would be working in. That distinction is the difference between a tool you work inside and a tool you work around.
What Credit Monitoring Actually Requires
Credit monitoring runs on three workflows that have no clean equivalent in equity portfolio management, and each one carries legal weight rather than reporting convenience. A direct lender with 40 borrowers and a dozen covenants per agreement tests hundreds of individually negotiated data points every quarter. None of those tests look like a quarterly mark, and getting one wrong creates liability, not a restated NAV.
Compliance certificate ingestion is the first workflow, and it sets the cadence of everything downstream. Borrowers deliver certificates and financial statements on deadlines written into each credit agreement, often 45, 60, or 90 days after quarter-end, with separate carve-outs for fiscal year-end reporting. Those financials arrive as PDFs over email and Excel files built on inconsistent charts of accounts, so an analyst has to spread them into structured data before any covenant can be tested. Ask whether a platform extracts borrower financials from unstructured PDFs and Excel files or relies on templates, because that decides whether the first step of the credit workflow happens inside the tool.
Covenant tracking across amendments is the second workflow, and it is where manual systems quietly produce wrong answers. Covenant levels step up or step down over a facility's life, waiver agreements suspend testing for defined periods, and financial definitions get renegotiated mid-deal. Definition drift is the failure mode here. EBITDA for covenant purposes might include management fees for one borrower and exclude them for another, depending on how each agreement was negotiated. A platform that stores one original covenant level and tests against it will pass a borrower who has already breached a stepped-down threshold.
Borrowing base certificate handling is the third workflow, and it sits alongside term loan covenants for asset-based facilities. These certificates arrive on their own cadence and require their own calculations, separate from the quarterly compliance certificate cycle. If a monitoring tool has no place for borrowing base certificates, they become a spreadsheet maintained next to the platform rather than inside it.
The cost of missing any of these is not a reporting delay. A missed violation lets a cure period run without your knowledge, and inaction can create waiver-by-conduct risk, where a lender is later deemed to have waived a breach and future enforcement becomes legally contested.
External pressure now makes systematic records non-optional. The SEC's 2024 examination priorities for private fund advisers named portfolio management risks from market volatility and higher interest rates, and the valuation of illiquid assets. For a credit manager, systematic covenant records are one way to show that oversight. LPs raise the same expectation during due diligence, where the ILPA DDQ is the standard industry questionnaire.
How Equity-First Platforms Handle Credit (and Where They Break)
A platform's origin story is worth understanding alongside its feature list, because the data model it grew up on shapes what comes naturally. Chronograph and 73 Strings both built real strengths over years of work, and a credit team should test how those strengths apply when it starts testing covenants.
Chronograph has spent a decade building portfolio monitoring, valuations, and analytics technology for LPs and GPs. Co-founder and CTO Michael Bridge says that getting "an answer you can fully trust and defend to an auditor, an LP, or an investment committee is the challenging part" (PR Newswire). The company calls its architecture a deterministic system of record at scale. Its private credit platform, launched in June 2026 alongside a growth equity investment of over $140 million from Sixth Street Growth, is described as a suite of purpose-built capabilities for private credit managers, and the company says the investment will accelerate the platform. Chronograph's private credit page describes borrower data collection, compliance certificate collection, covenant monitoring, and add-backs checked against negotiated caps (Chronograph). A credit team should ask to see how covenant tests run against amendment-adjusted levels and how breaches are surfaced.
73 Strings organizes its platform into 73 Extract, 73 Monitor and 73 Value and positions itself around valuation. The company says it serves both equity and credit, lists private debt among its specialties, and its private credit page describes covenant compliance tracking and extraction from credit agreements and financial statements (73 Strings). Its Series B roadmap, funded by a $55 million round in early 2025, names portfolio simulation, sensitivity analysis, and benchmarking.
The consequence shows up in the analyst's day. Ask whether the platform runs covenant calculations against amendment-adjusted levels or only stores the terms, whether compliance certificates are collected through a borrower-facing workflow with deadline reminders, and where borrowing base certificates live. If any of these happens in a spreadsheet alongside the tool, each workaround recreates the problem the platform was supposed to solve. A platform you work around is a platform that left the hard part of credit to you.
What a Credit-Native Data Model Looks Like in Practice
A credit-native platform organizes everything around the loan, and the difference shows up at three touchpoints.
The first is compliance certificate ingestion with source-cell traceability. When a borrower submits a compliance certificate, Lumonic extracts the financials and tests the covenants, and every figure traces back to the cell it came from in the source document (Lumonic private credit). An analyst checking a leverage covenant can click the calculated debt-to-EBITDA ratio and see exactly which line items fed it, which means discrepancies surface during review rather than during an audit. Ask whether a platform calculates from the certificate or stores it as a document and leaves the calculation to a spreadsheet, which breaks the trail between the number and its origin.
The second is amendment-aware covenant tracking. Covenant levels rarely stay fixed over a facility's life, and a leverage threshold that starts at 5.0x in year one might step down to 4.5x in year two, then sit under a waiver for two quarters after an acquisition. Lumonic stores these terms per borrower, including amendments and the borrower-specific EBITDA definition that decides whether management fees or restructuring charges count (covenant tracking). A correct compliance assessment tests the borrower against the current contractual level. A platform that holds a single static covenant value tests against the wrong number the moment an amendment lands.
The third is borrowing base certificate handling sitting alongside term loan covenants. Asset-based facilities run on a different cadence than maintenance covenants, and the borrowing base certificate reports eligible receivables and inventory against advance rates on its own schedule. Lumonic ingests borrowing base certificates and term loan compliance certificates within the same data model, so a manager running both structures across a portfolio works in one place rather than splitting attention between the tool and a parallel tracker (Lumonic private credit).
The operational payoff appears in turnaround time. At Avante Capital Partners, portfolio review preparation that previously took two to three weeks dropped to two to three days. When the platform already understands what a compliance certificate is and how a covenant calculates, the analyst spends time on judgment rather than reassembly, and the firm produces the systematic records an examiner expects without a reformatting scramble.
Questions to Ask at Any Platform Demo
Before you sit through another platform demo, write down the questions that separate a credit-native tool from one wearing a credit costume. A polished interface can hide a data model that was never built for the loan lifecycle. The answers to these questions surface that gap fast.
Does covenant testing run the calculation, or just store the terms?
Storing a 3.5x debt-to-EBITDA threshold is bookkeeping. You need the platform to ingest the borrower's financials, compute the actual ratio, and tell you the cushion. Ask the demo team to run a live test against real numbers, not a static term sheet.
Can it spread financials from an unstructured PDF?
Borrowers send financials as PDFs over email and Excel files with inconsistent charts of accounts. If data only enters through templates the platform provides, you will be retyping numbers by hand. Ask whether financial spreading happens through extraction or through manual entry.
How does it handle a covenant step-down in year two?
Many facilities tighten the leverage threshold over the term. A system that tests current financials against original levels produces a wrong answer the moment that step-down hits. Ask them to walk through a facility where the covenant level changes and a waiver suspends testing for one quarter.
What happens when a borrower misses a compliance certificate deadline?
Credit agreements specify delivery windows, often 45, 60, or 90 days after quarter-end. Ask whether the platform sends automated reminders, escalates the miss, and logs it. Silence on a missed certificate creates waiver-by-conduct risk if you appear to have tolerated a breach.
Is every calculation traceable to its source document?
When an LP or auditor asks how you arrived at a covenant result, you need to click from the number to the exact cell in the borrower's statement. Ask to see source-cell traceability in action, not a screenshot.
Can it produce audit-ready output for an SEC examiner?
The SEC's 2024 exam priorities named valuation and portfolio management risk at private fund advisers. Ask whether the platform exports systematic records of testing, certificate receipt, and breach timelines without manual reformatting. If the answer involves a spreadsheet export and cleanup, the data model is working against you.
Conclusion
Choosing a monitoring platform is a data model decision, and a data model decision compounds. The architecture you pick today shapes every covenant test, certificate ingestion, and breach alert you run for the life of the facility.
Ask each platform what sits at the center of its data model. If valuation sits at the center and credit features hang off the edges, analysts end up closing the gap between what the tool models and what the credit agreement demands.
Lumonic builds from the loan lifecycle outward, with compliance certificate ingestion, amendment-aware covenant tracking, and source-cell traceability at the core of the product (lumonic.com). When you evaluate a platform, look past the credit features in the demo and ask what the data model was designed to do. The answer predicts everything that follows.
Disclaimer
This article was written by Lumonic, a PitchBook company, and reflects Lumonic's views as of October 2026. Statements about third-party products and companies are based on publicly available information, including the vendors' own websites, press releases and documentation, and on the sources linked in the text. Lumonic has not independently tested third-party products, and their capabilities, pricing and positioning may have changed since this article was last updated. Statements about Lumonic's own product describe the platform at the time of writing, and customer outcomes are taken from the published customer stories linked in the text. Nothing here is a guarantee of results. Third-party names and trademarks belong to their respective owners and are used for identification only. If you represent a company named here and believe a statement is inaccurate, contact support@lumonic.com and we will review and correct it.
Credit-Native Portfolio Monitoring vs Equity-First Platforms: why private credit needs credit-native monitoring
TLDR
Private credit monitoring runs on the loan lifecycle, where covenant testing is a legal obligation tested on a fixed cadence, not a quarterly mark like the IRR-driven workflows equity platforms were built around.
Chronograph and 73 Strings serve both equity and credit managers. Chronograph launched a private credit platform in June 2026, and 73 Strings positions itself around valuation, so buyers should ask each how covenant testing and certificate handling fit its data model.
The data model shows up in daily work: ask how each platform handles compliance certificates, borrowing base certificates, and covenant step-downs across amendments without a spreadsheet alongside it.
Lumonic is the system of record for credit and equity fund portfolios, with covenant tracking, compliance certificate ingestion, and source-cell traceability organized around the loan lifecycle.
The Wrong Data Model Is the Problem, Not the Feature Gap
A monitoring platform's data model decides what it does natively and what it can only approximate through workarounds. Before you compare feature lists, look at the endpoint each platform is built to reach. An equity-first tool organizes everything around a quarterly mark. A credit-native tool organizes everything around a loan that has obligations testing on a schedule the borrower controls.
These two endpoints pull a platform's architecture in opposite directions. A valuation engine treats data as inputs that resolve into a defensible number every 90 days, so versioning, point-in-time reproducibility, and IRR rollups become the hard problems worth solving. Credit monitoring runs on a different clock. A debt-to-EBITDA breach forces an enforcement decision within days, not at the next review cycle, and a missed compliance certificate starts cure periods running without your knowledge. The data model has to treat covenant obligations and delivery deadlines as first-class objects, not as fields attached to a valuation record.
Chronograph describes its architecture as a deterministic system of record with full versioning and point-in-time reproducibility for data. That is genuine engineering, built over a decade. For a credit team, the question to ask is how that architecture handles detecting a breach between reporting periods.
73 Strings organizes its platform into three products, 73 Extract, 73 Monitor and 73 Value, and positions itself as "the valuation technology moving private markets forward" (73 Strings). Buyers should ask how covenant testing fits alongside the valuation workflow.
Neither platform is weak at what it was designed for. Both now market private credit capabilities, so the useful test is whether covenant compliance, certificate ingestion, and borrowing base tracking sit at the center of the data model you would be working in. That distinction is the difference between a tool you work inside and a tool you work around.
What Credit Monitoring Actually Requires
Credit monitoring runs on three workflows that have no clean equivalent in equity portfolio management, and each one carries legal weight rather than reporting convenience. A direct lender with 40 borrowers and a dozen covenants per agreement tests hundreds of individually negotiated data points every quarter. None of those tests look like a quarterly mark, and getting one wrong creates liability, not a restated NAV.
Compliance certificate ingestion is the first workflow, and it sets the cadence of everything downstream. Borrowers deliver certificates and financial statements on deadlines written into each credit agreement, often 45, 60, or 90 days after quarter-end, with separate carve-outs for fiscal year-end reporting. Those financials arrive as PDFs over email and Excel files built on inconsistent charts of accounts, so an analyst has to spread them into structured data before any covenant can be tested. Ask whether a platform extracts borrower financials from unstructured PDFs and Excel files or relies on templates, because that decides whether the first step of the credit workflow happens inside the tool.
Covenant tracking across amendments is the second workflow, and it is where manual systems quietly produce wrong answers. Covenant levels step up or step down over a facility's life, waiver agreements suspend testing for defined periods, and financial definitions get renegotiated mid-deal. Definition drift is the failure mode here. EBITDA for covenant purposes might include management fees for one borrower and exclude them for another, depending on how each agreement was negotiated. A platform that stores one original covenant level and tests against it will pass a borrower who has already breached a stepped-down threshold.
Borrowing base certificate handling is the third workflow, and it sits alongside term loan covenants for asset-based facilities. These certificates arrive on their own cadence and require their own calculations, separate from the quarterly compliance certificate cycle. If a monitoring tool has no place for borrowing base certificates, they become a spreadsheet maintained next to the platform rather than inside it.
The cost of missing any of these is not a reporting delay. A missed violation lets a cure period run without your knowledge, and inaction can create waiver-by-conduct risk, where a lender is later deemed to have waived a breach and future enforcement becomes legally contested.
External pressure now makes systematic records non-optional. The SEC's 2024 examination priorities for private fund advisers named portfolio management risks from market volatility and higher interest rates, and the valuation of illiquid assets. For a credit manager, systematic covenant records are one way to show that oversight. LPs raise the same expectation during due diligence, where the ILPA DDQ is the standard industry questionnaire.
How Equity-First Platforms Handle Credit (and Where They Break)
A platform's origin story is worth understanding alongside its feature list, because the data model it grew up on shapes what comes naturally. Chronograph and 73 Strings both built real strengths over years of work, and a credit team should test how those strengths apply when it starts testing covenants.
Chronograph has spent a decade building portfolio monitoring, valuations, and analytics technology for LPs and GPs. Co-founder and CTO Michael Bridge says that getting "an answer you can fully trust and defend to an auditor, an LP, or an investment committee is the challenging part" (PR Newswire). The company calls its architecture a deterministic system of record at scale. Its private credit platform, launched in June 2026 alongside a growth equity investment of over $140 million from Sixth Street Growth, is described as a suite of purpose-built capabilities for private credit managers, and the company says the investment will accelerate the platform. Chronograph's private credit page describes borrower data collection, compliance certificate collection, covenant monitoring, and add-backs checked against negotiated caps (Chronograph). A credit team should ask to see how covenant tests run against amendment-adjusted levels and how breaches are surfaced.
73 Strings organizes its platform into 73 Extract, 73 Monitor and 73 Value and positions itself around valuation. The company says it serves both equity and credit, lists private debt among its specialties, and its private credit page describes covenant compliance tracking and extraction from credit agreements and financial statements (73 Strings). Its Series B roadmap, funded by a $55 million round in early 2025, names portfolio simulation, sensitivity analysis, and benchmarking.
The consequence shows up in the analyst's day. Ask whether the platform runs covenant calculations against amendment-adjusted levels or only stores the terms, whether compliance certificates are collected through a borrower-facing workflow with deadline reminders, and where borrowing base certificates live. If any of these happens in a spreadsheet alongside the tool, each workaround recreates the problem the platform was supposed to solve. A platform you work around is a platform that left the hard part of credit to you.
What a Credit-Native Data Model Looks Like in Practice
A credit-native platform organizes everything around the loan, and the difference shows up at three touchpoints.
The first is compliance certificate ingestion with source-cell traceability. When a borrower submits a compliance certificate, Lumonic extracts the financials and tests the covenants, and every figure traces back to the cell it came from in the source document (Lumonic private credit). An analyst checking a leverage covenant can click the calculated debt-to-EBITDA ratio and see exactly which line items fed it, which means discrepancies surface during review rather than during an audit. Ask whether a platform calculates from the certificate or stores it as a document and leaves the calculation to a spreadsheet, which breaks the trail between the number and its origin.
The second is amendment-aware covenant tracking. Covenant levels rarely stay fixed over a facility's life, and a leverage threshold that starts at 5.0x in year one might step down to 4.5x in year two, then sit under a waiver for two quarters after an acquisition. Lumonic stores these terms per borrower, including amendments and the borrower-specific EBITDA definition that decides whether management fees or restructuring charges count (covenant tracking). A correct compliance assessment tests the borrower against the current contractual level. A platform that holds a single static covenant value tests against the wrong number the moment an amendment lands.
The third is borrowing base certificate handling sitting alongside term loan covenants. Asset-based facilities run on a different cadence than maintenance covenants, and the borrowing base certificate reports eligible receivables and inventory against advance rates on its own schedule. Lumonic ingests borrowing base certificates and term loan compliance certificates within the same data model, so a manager running both structures across a portfolio works in one place rather than splitting attention between the tool and a parallel tracker (Lumonic private credit).
The operational payoff appears in turnaround time. At Avante Capital Partners, portfolio review preparation that previously took two to three weeks dropped to two to three days. When the platform already understands what a compliance certificate is and how a covenant calculates, the analyst spends time on judgment rather than reassembly, and the firm produces the systematic records an examiner expects without a reformatting scramble.
Questions to Ask at Any Platform Demo
Before you sit through another platform demo, write down the questions that separate a credit-native tool from one wearing a credit costume. A polished interface can hide a data model that was never built for the loan lifecycle. The answers to these questions surface that gap fast.
Does covenant testing run the calculation, or just store the terms?
Storing a 3.5x debt-to-EBITDA threshold is bookkeeping. You need the platform to ingest the borrower's financials, compute the actual ratio, and tell you the cushion. Ask the demo team to run a live test against real numbers, not a static term sheet.
Can it spread financials from an unstructured PDF?
Borrowers send financials as PDFs over email and Excel files with inconsistent charts of accounts. If data only enters through templates the platform provides, you will be retyping numbers by hand. Ask whether financial spreading happens through extraction or through manual entry.
How does it handle a covenant step-down in year two?
Many facilities tighten the leverage threshold over the term. A system that tests current financials against original levels produces a wrong answer the moment that step-down hits. Ask them to walk through a facility where the covenant level changes and a waiver suspends testing for one quarter.
What happens when a borrower misses a compliance certificate deadline?
Credit agreements specify delivery windows, often 45, 60, or 90 days after quarter-end. Ask whether the platform sends automated reminders, escalates the miss, and logs it. Silence on a missed certificate creates waiver-by-conduct risk if you appear to have tolerated a breach.
Is every calculation traceable to its source document?
When an LP or auditor asks how you arrived at a covenant result, you need to click from the number to the exact cell in the borrower's statement. Ask to see source-cell traceability in action, not a screenshot.
Can it produce audit-ready output for an SEC examiner?
The SEC's 2024 exam priorities named valuation and portfolio management risk at private fund advisers. Ask whether the platform exports systematic records of testing, certificate receipt, and breach timelines without manual reformatting. If the answer involves a spreadsheet export and cleanup, the data model is working against you.
Conclusion
Choosing a monitoring platform is a data model decision, and a data model decision compounds. The architecture you pick today shapes every covenant test, certificate ingestion, and breach alert you run for the life of the facility.
Ask each platform what sits at the center of its data model. If valuation sits at the center and credit features hang off the edges, analysts end up closing the gap between what the tool models and what the credit agreement demands.
Lumonic builds from the loan lifecycle outward, with compliance certificate ingestion, amendment-aware covenant tracking, and source-cell traceability at the core of the product (lumonic.com). When you evaluate a platform, look past the credit features in the demo and ask what the data model was designed to do. The answer predicts everything that follows.
Disclaimer
This article was written by Lumonic, a PitchBook company, and reflects Lumonic's views as of October 2026. Statements about third-party products and companies are based on publicly available information, including the vendors' own websites, press releases and documentation, and on the sources linked in the text. Lumonic has not independently tested third-party products, and their capabilities, pricing and positioning may have changed since this article was last updated. Statements about Lumonic's own product describe the platform at the time of writing, and customer outcomes are taken from the published customer stories linked in the text. Nothing here is a guarantee of results. Third-party names and trademarks belong to their respective owners and are used for identification only. If you represent a company named here and believe a statement is inaccurate, contact support@lumonic.com and we will review and correct it.
