TL;DR
This ranking judges platforms on one job, getting portfolio company financials out of PDFs, spreadsheets, and scanned statements into structured data without an analyst chasing emails. It is not a general fund administration comparison.
Lumonic tops this list: it reads non-standardized submissions, extracts the numbers the way the firm decided once, and traces every figure back to the page and cell it came from.
iLEVEL offers a long-established cross-portfolio data model, and S&P Global announced Automated Data Ingestion in February 2025 for AI extraction and recurring per-company document collection.
Standard Metrics handles venture-style KPI collection well; PE buyers should ask how it handles complex structures.
73 Strings brings extraction breadth alongside valuation and monitoring modules; ask about implementation scope.
Cobalt (FactSet) announced AI Doc Ingest in February 2026 for extraction from PDFs, Excel files and board decks.
Atominvest, FundCount, and Allvue offer monitoring or document extraction as part of broader fund management suites.
Why portfolio data collection breaks down at scale
Portfolio companies may submit PDFs, scanned statements or spreadsheets with different layouts. When a platform cannot extract those figures or track submissions, an analyst must enter the data and follow up with companies. A dashboard alone does not remove either task.
Evaluate how each platform handles incoming formats, extracts figures, tracks submissions and traces results to their source. Format handling covers whether the system reads non-standardized documents or forces companies into rigid templates. Extraction versus template entry determines who does the typing. Submission tracking and reminders decide whether analysts chase delinquent companies by hand. Auditability confirms each figure traces back to its source document.
This comparison focuses on collection and ingestion rather than every portfolio monitoring feature.
Comparison table
Platform | Best For | Format Handling | Key Strengths | Limitations |
|---|---|---|---|---|
Lumonic | Credit and equity funds that want the monitoring work done inside the system of record, with every number staged for review and traced to its page | PDF, Excel, scanned docs, non-standardized submissions | Extraction the way the firm decided once, reminder workflows, submission tracking, every number traced to its page | Newer entrant vs. incumbents |
iLEVEL | Firms wanting a mature cross-portfolio data model | AI extraction from PDFs and spreadsheets (Automated Data Ingestion, announced February 2025) | Standardized chart of accounts, click-to-data-trace, recurring per-company collection workflows, Managed Data Services | Lumonic has not tested ADI; run it on your own documents |
Standard Metrics | Early-stage VC and lighter KPI portfolios | AI and human-in-the-loop parsing of board decks and financial statements | Many-to-many reporting, submission tracking | Ask about complex PE structures and covenant workflows |
73 Strings | Firms that want extraction, monitoring and valuation from one vendor | AI extraction across document types | Broad extraction, valuation depth | Ask about implementation scope and partner involvement |
Cobalt | FactSet-ecosystem firms | Portfolio company data collection plus AI Doc Ingest for PDFs, Excel and board decks (announced February 2026) | Portfolio monitoring, FactSet data, extracted values traceable to source | Confirm AI Doc Ingest availability for your region |
Atominvest | Firms wanting one platform across functions | AI extraction from Excel, PDFs, board decks and lender packages (per vendor) | Investor management, fund accounting breadth | Test extraction on your own documents |
FundCount | Firms prioritizing fund accounting continuity | Document intelligence for fund documents and financial statements, including unstructured PDFs | Accounting and fund administration | Not positioned primarily as portfolio monitoring software (per vendor) |
Allvue | Large firms wanting a single enterprise suite | KPI templates, Excel mapping wizard, Document IQ extraction | Full fund lifecycle coverage | Ask about implementation scope for the modules you need |
Lumonic
Lumonic replaces the template-and-email collection model that many PE monitoring teams run on. Portfolio companies send financials in whatever format they keep them, and Lumonic ingests non-standardized submissions directly, whether that arrives as a PDF, an Excel file with inconsistent tabs, or a scanned document. The extraction engine reads those files and maps the numbers into a structured format without an analyst rekeying line items. That handles a failure mode the WorkWise article describes, where firms adopt a platform and are back in Excel months later because the tool did not change how they worked.
Chasing delinquent portfolio companies is where analyst time disappears, and Lumonic automates the follow-up. The platform sends scheduled reminders to companies that owe reporting, then tracks who has submitted and who has not on a submission dashboard. You see the status of every request in one view rather than reconstructing it from a sent-mail folder.
Every extracted number links back to the cell or line in the original document it came from. When a figure looks wrong or an LP asks where it originated, you click the value and see the source page rather than trusting an unlabeled import. Source-cell traceability answers the provenance question that template-based entry cannot, because manual re-entry breaks the chain between the number in your system and the document it was pulled from.
For portfolio companies that carry debt, Lumonic also surfaces covenant and debt-compliance visibility as part of the same collection workflow. Once financials are ingested and structured, the platform can check them against covenant thresholds without a separate reconciliation step. That capability is a bonus for debt-carrying holdings, not the primary reason to adopt the platform.
Lumonic serves lower middle market PE firms and institutional investors. Buyers with large portfolios should confirm collection volume, approval workflows and implementation requirements during a pilot.
Best for: PE firms replacing manual, email-driven collection with extraction that carries the firm's decisions forward, with every number staged for review and traced to its page.
iLEVEL
S&P iLEVEL is one of the longest-established platforms in portfolio monitoring and remains an institutional standard for multi-portfolio analytics. Its flexible data model maps portfolio company financials to a standard chart of accounts, which lets a firm compare metrics across hundreds of holdings on a consistent basis. For firms that value a mature, standardized cross-portfolio data model, iLEVEL delivers on centralization.
Across private markets, investment information is often spread across "numerous fund manager portals, individual emails, static PDFs, and disparate internal spreadsheets" (Carta). For that collection step, S&P Global announced Automated Data Ingestion for iLEVEL in February 2025, which uses AI to extract structured and unstructured data from PDFs and spreadsheets, runs recurring collection workflows configured once per portfolio company, and gives click-to-data-trace access to the original document. In August 2025 it added iLEVEL Document Search and listed Covenant Monitoring and Financial Spreading as part of iLEVEL Credit. Lumonic has not independently tested these capabilities.
iLEVEL also offers Managed Data Services for firms without internal bandwidth, which S&P describes as combining data ingestion technology with human-in-the-loop review to collect and normalize data from source documents (S&P Global).
Best for: firms that want a mature, standardized cross-portfolio data model from a long-established vendor.
Standard Metrics
Standard Metrics collects venture-style KPIs at scale, and its own numbers explain the fit. The company reports 150+ venture capital and private equity firms and 10,000+ companies on the platform, naming Lux Capital, General Catalyst, Accel, and Bessemer among its customers (Standard Metrics). Its AI parsing layer ingests financial statements, KPI reports, and cap table updates across PDFs, Excel files, and slide decks, backed by a human data-services team for edge cases (vcsoftware.vc). Standard Metrics also offers an AI Analyst that answers natural-language questions across portfolio data.
Standard Metrics' many-to-many reporting model is relevant to companies that share updates with multiple investors. PE buyers should also test multi-entity reporting and any covenant workflows they require. Public material cited here does not establish how those workflows operate.
Best for: early-stage VC and lighter KPI portfolios. PE firms with multi-entity consolidations or covenant schedules should confirm those workflows directly.
73 Strings
73 Strings extracts data from portfolio company documents and positions itself around valuation, describing itself as "the valuation technology moving private markets forward", with extraction (73 Extract), monitoring (73 Monitor) and valuation (73 Value) modules (73 Strings). Its 73 Extract module "captures and harmonizes hundreds of financial and operational data points and KPIs" across companies that report in different formats (73 Strings).
Buyers should ask about implementation scope, partner involvement and total cost.
Best for: firms that want extraction, monitoring and valuation from one vendor.
Cobalt
Cobalt is FactSet's portfolio monitoring platform. FactSet's AI Doc Ingest announcement describes a newer document extraction capability.
FactSet announced AI Doc Ingest for Cobalt in beta on February 4, 2026, moving toward extraction rather than manual entry. The add-on is described as pulling data from PDFs, Excel files, and board decks, mapping it into a client-defined data model, and tracing extracted values back to source documents. FactSet initially released it to select North American clients and said general availability was scheduled for March 2026, with a European rollout planned for late spring 2026; buyers should confirm current availability.
Ask FactSet how AI Doc Ingest handles your firm's document types and whether it is available in your region.
Best for: FactSet-ecosystem firms that want portfolio monitoring connected to FactSet data.
Atominvest
Atominvest builds a broad asset-management platform where portfolio monitoring sits alongside fund accounting and investor management modules. The company markets its software to private equity, credit, growth equity, and venture firms, describing portfolio monitoring as collecting key metrics through customized dashboard views (Built In NYC). Its platform scope reaches beyond collection into fundraising datarooms, capital call notices, and ESG questionnaires.
The company's own materials mention "flexible data ingestion and automated workflows for efficient metric collection," and its portfolio management page says it ingests financials, KPIs and covenants from Excel, PDFs, board decks and lender packages using AI extraction, with audit trails and configurable approval workflows (Atominvest). We did not find public detail on how it tracks and follows up on late submissions. Buyers evaluating Atominvest on collection depth specifically will need to verify those mechanics directly with the vendor.
Best for: firms that want one platform spanning investor management, fund accounting, and portfolio monitoring rather than a specialized data collection tool.
FundCount
FundCount emphasizes accounting and fund administration in its product positioning. Its own comparison materials state the platform "is not positioned primarily as portfolio monitoring software," with strength in "accounting-backed portfolio accounting, performance measures, attribution, partnership accounting, reporting, document intelligence, and investor delivery" (FundCount vs Allvue). Buyers needing portfolio company KPI collection should test that workflow separately.
FundCount does offer document intelligence that extracts fields from capital calls, distributions, capital-account and co-investment statements, invoices and financial statements, including unstructured PDFs in formats it has not seen before. We did not find FundCount material on covenant compliance certificate ingestion or debt-schedule tracking for portfolio companies carrying debt.
Best for: firms prioritizing fund accounting and reporting continuity over specialized portfolio company data extraction.
Allvue
Allvue sells a broad enterprise suite that spans fund accounting, investor relations, and portfolio monitoring, marketing itself as alternative investment software for the full fund lifecycle. Allvue's site groups data collection with its Portfolio Monitoring product.
Allvue describes configurable KPI templates for portfolio company collection. Allvue's own demo describes a portal where each portfolio company fills out a configurable KPI template, backed by an Excel mapping wizard for less standardized inputs. A newer Document IQ layer extracts data from financials, loan notices, and credit agreements, and Allvue describes its document extraction as covering financials that borrowers, administrators, and portfolio companies deliver in inconsistent formats (Allvue).
Buyers should ask about implementation scope and timeline for the modules they need.
Best for: large firms that want one platform across fund accounting, investor relations, and portfolio monitoring.
What to look for in a data collection platform
Start with format handling, extraction, submission follow-up and source traceback. Then test the monitoring workflows your PE firm needs, including approvals, covenant visibility for debt-carrying companies and LP reporting.
Format flexibility. Portfolio companies send financials as PDFs, scanned statements, and spreadsheets with inconsistent layouts. A platform that only accepts formatted CSV or Excel templates pushes the reformatting work back onto your analysts, who then re-key numbers by hand. Ask the vendor to ingest a messy scanned statement during the demo, not a clean template.
Submission tracking and reminders. Someone has to know which portfolio companies have reported and which are late. Without automated tracking dashboards and reminder workflows, an analyst spends the quarter sending follow-up emails and chasing delinquent submissions manually. Confirm the platform tracks status per company and sends reminders without a human triggering each one.
Extraction versus template-based entry. Templates require someone to map information into predefined fields. Ask each vendor to extract figures from an unfamiliar document, show how your mapping decisions carry forward and identify what needs human review. Confirm which capabilities are generally available.
Auditability and source traceability. Ask each vendor to trace a dashboard figure to its source page and show the calculation rules carried forward. Check who reviews staged results, who can publish them and whether the system of record retains threshold and amendment history.
Conclusion
Lumonic is built around the one task this list measures. Portfolio companies send financials as PDFs, scanned statements, and spreadsheets that never match a template, and Lumonic reads those files directly, extracts the numbers, and maps them into structured fields without an analyst retyping anything. Automated reminders and a submission tracking dashboard chase delinquent companies so your team stops doing it by hand. Every extracted figure links back to the exact cell in the original document, so a reviewer can verify a number in seconds.
FAQs
How is PE data collection different from LP reporting software? PE data collection pulls financials and KPIs inbound from portfolio companies into a structured format. LP reporting sends fund performance outbound to investors. Lumonic handles the inbound collection job, extracting non-standardized submissions before that data ever reaches an LP report.
Is AI extraction reliable enough to replace manual entry? AI extraction reads source documents and pulls out numbers without manual re-keying. Lumonic pairs that extraction with source-cell traceability and human review of flagged exceptions rather than a black box. The result is handling of PDFs, Excel files, and scanned documents with every value staged for review and verifiable against its origin.
What does source-cell traceability mean in practice? Every extracted figure links back to the exact cell or line in the original document. Lumonic stores that link so an analyst can click a number in the dashboard and see its source. It prevents untraceable numbers and makes audit review fast instead of forensic.
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.
TL;DR
This ranking judges platforms on one job, getting portfolio company financials out of PDFs, spreadsheets, and scanned statements into structured data without an analyst chasing emails. It is not a general fund administration comparison.
Lumonic tops this list: it reads non-standardized submissions, extracts the numbers the way the firm decided once, and traces every figure back to the page and cell it came from.
iLEVEL offers a long-established cross-portfolio data model, and S&P Global announced Automated Data Ingestion in February 2025 for AI extraction and recurring per-company document collection.
Standard Metrics handles venture-style KPI collection well; PE buyers should ask how it handles complex structures.
73 Strings brings extraction breadth alongside valuation and monitoring modules; ask about implementation scope.
Cobalt (FactSet) announced AI Doc Ingest in February 2026 for extraction from PDFs, Excel files and board decks.
Atominvest, FundCount, and Allvue offer monitoring or document extraction as part of broader fund management suites.
Why portfolio data collection breaks down at scale
Portfolio companies may submit PDFs, scanned statements or spreadsheets with different layouts. When a platform cannot extract those figures or track submissions, an analyst must enter the data and follow up with companies. A dashboard alone does not remove either task.
Evaluate how each platform handles incoming formats, extracts figures, tracks submissions and traces results to their source. Format handling covers whether the system reads non-standardized documents or forces companies into rigid templates. Extraction versus template entry determines who does the typing. Submission tracking and reminders decide whether analysts chase delinquent companies by hand. Auditability confirms each figure traces back to its source document.
This comparison focuses on collection and ingestion rather than every portfolio monitoring feature.
Comparison table
Platform | Best For | Format Handling | Key Strengths | Limitations |
|---|---|---|---|---|
Lumonic | Credit and equity funds that want the monitoring work done inside the system of record, with every number staged for review and traced to its page | PDF, Excel, scanned docs, non-standardized submissions | Extraction the way the firm decided once, reminder workflows, submission tracking, every number traced to its page | Newer entrant vs. incumbents |
iLEVEL | Firms wanting a mature cross-portfolio data model | AI extraction from PDFs and spreadsheets (Automated Data Ingestion, announced February 2025) | Standardized chart of accounts, click-to-data-trace, recurring per-company collection workflows, Managed Data Services | Lumonic has not tested ADI; run it on your own documents |
Standard Metrics | Early-stage VC and lighter KPI portfolios | AI and human-in-the-loop parsing of board decks and financial statements | Many-to-many reporting, submission tracking | Ask about complex PE structures and covenant workflows |
73 Strings | Firms that want extraction, monitoring and valuation from one vendor | AI extraction across document types | Broad extraction, valuation depth | Ask about implementation scope and partner involvement |
Cobalt | FactSet-ecosystem firms | Portfolio company data collection plus AI Doc Ingest for PDFs, Excel and board decks (announced February 2026) | Portfolio monitoring, FactSet data, extracted values traceable to source | Confirm AI Doc Ingest availability for your region |
Atominvest | Firms wanting one platform across functions | AI extraction from Excel, PDFs, board decks and lender packages (per vendor) | Investor management, fund accounting breadth | Test extraction on your own documents |
FundCount | Firms prioritizing fund accounting continuity | Document intelligence for fund documents and financial statements, including unstructured PDFs | Accounting and fund administration | Not positioned primarily as portfolio monitoring software (per vendor) |
Allvue | Large firms wanting a single enterprise suite | KPI templates, Excel mapping wizard, Document IQ extraction | Full fund lifecycle coverage | Ask about implementation scope for the modules you need |
Lumonic
Lumonic replaces the template-and-email collection model that many PE monitoring teams run on. Portfolio companies send financials in whatever format they keep them, and Lumonic ingests non-standardized submissions directly, whether that arrives as a PDF, an Excel file with inconsistent tabs, or a scanned document. The extraction engine reads those files and maps the numbers into a structured format without an analyst rekeying line items. That handles a failure mode the WorkWise article describes, where firms adopt a platform and are back in Excel months later because the tool did not change how they worked.
Chasing delinquent portfolio companies is where analyst time disappears, and Lumonic automates the follow-up. The platform sends scheduled reminders to companies that owe reporting, then tracks who has submitted and who has not on a submission dashboard. You see the status of every request in one view rather than reconstructing it from a sent-mail folder.
Every extracted number links back to the cell or line in the original document it came from. When a figure looks wrong or an LP asks where it originated, you click the value and see the source page rather than trusting an unlabeled import. Source-cell traceability answers the provenance question that template-based entry cannot, because manual re-entry breaks the chain between the number in your system and the document it was pulled from.
For portfolio companies that carry debt, Lumonic also surfaces covenant and debt-compliance visibility as part of the same collection workflow. Once financials are ingested and structured, the platform can check them against covenant thresholds without a separate reconciliation step. That capability is a bonus for debt-carrying holdings, not the primary reason to adopt the platform.
Lumonic serves lower middle market PE firms and institutional investors. Buyers with large portfolios should confirm collection volume, approval workflows and implementation requirements during a pilot.
Best for: PE firms replacing manual, email-driven collection with extraction that carries the firm's decisions forward, with every number staged for review and traced to its page.
iLEVEL
S&P iLEVEL is one of the longest-established platforms in portfolio monitoring and remains an institutional standard for multi-portfolio analytics. Its flexible data model maps portfolio company financials to a standard chart of accounts, which lets a firm compare metrics across hundreds of holdings on a consistent basis. For firms that value a mature, standardized cross-portfolio data model, iLEVEL delivers on centralization.
Across private markets, investment information is often spread across "numerous fund manager portals, individual emails, static PDFs, and disparate internal spreadsheets" (Carta). For that collection step, S&P Global announced Automated Data Ingestion for iLEVEL in February 2025, which uses AI to extract structured and unstructured data from PDFs and spreadsheets, runs recurring collection workflows configured once per portfolio company, and gives click-to-data-trace access to the original document. In August 2025 it added iLEVEL Document Search and listed Covenant Monitoring and Financial Spreading as part of iLEVEL Credit. Lumonic has not independently tested these capabilities.
iLEVEL also offers Managed Data Services for firms without internal bandwidth, which S&P describes as combining data ingestion technology with human-in-the-loop review to collect and normalize data from source documents (S&P Global).
Best for: firms that want a mature, standardized cross-portfolio data model from a long-established vendor.
Standard Metrics
Standard Metrics collects venture-style KPIs at scale, and its own numbers explain the fit. The company reports 150+ venture capital and private equity firms and 10,000+ companies on the platform, naming Lux Capital, General Catalyst, Accel, and Bessemer among its customers (Standard Metrics). Its AI parsing layer ingests financial statements, KPI reports, and cap table updates across PDFs, Excel files, and slide decks, backed by a human data-services team for edge cases (vcsoftware.vc). Standard Metrics also offers an AI Analyst that answers natural-language questions across portfolio data.
Standard Metrics' many-to-many reporting model is relevant to companies that share updates with multiple investors. PE buyers should also test multi-entity reporting and any covenant workflows they require. Public material cited here does not establish how those workflows operate.
Best for: early-stage VC and lighter KPI portfolios. PE firms with multi-entity consolidations or covenant schedules should confirm those workflows directly.
73 Strings
73 Strings extracts data from portfolio company documents and positions itself around valuation, describing itself as "the valuation technology moving private markets forward", with extraction (73 Extract), monitoring (73 Monitor) and valuation (73 Value) modules (73 Strings). Its 73 Extract module "captures and harmonizes hundreds of financial and operational data points and KPIs" across companies that report in different formats (73 Strings).
Buyers should ask about implementation scope, partner involvement and total cost.
Best for: firms that want extraction, monitoring and valuation from one vendor.
Cobalt
Cobalt is FactSet's portfolio monitoring platform. FactSet's AI Doc Ingest announcement describes a newer document extraction capability.
FactSet announced AI Doc Ingest for Cobalt in beta on February 4, 2026, moving toward extraction rather than manual entry. The add-on is described as pulling data from PDFs, Excel files, and board decks, mapping it into a client-defined data model, and tracing extracted values back to source documents. FactSet initially released it to select North American clients and said general availability was scheduled for March 2026, with a European rollout planned for late spring 2026; buyers should confirm current availability.
Ask FactSet how AI Doc Ingest handles your firm's document types and whether it is available in your region.
Best for: FactSet-ecosystem firms that want portfolio monitoring connected to FactSet data.
Atominvest
Atominvest builds a broad asset-management platform where portfolio monitoring sits alongside fund accounting and investor management modules. The company markets its software to private equity, credit, growth equity, and venture firms, describing portfolio monitoring as collecting key metrics through customized dashboard views (Built In NYC). Its platform scope reaches beyond collection into fundraising datarooms, capital call notices, and ESG questionnaires.
The company's own materials mention "flexible data ingestion and automated workflows for efficient metric collection," and its portfolio management page says it ingests financials, KPIs and covenants from Excel, PDFs, board decks and lender packages using AI extraction, with audit trails and configurable approval workflows (Atominvest). We did not find public detail on how it tracks and follows up on late submissions. Buyers evaluating Atominvest on collection depth specifically will need to verify those mechanics directly with the vendor.
Best for: firms that want one platform spanning investor management, fund accounting, and portfolio monitoring rather than a specialized data collection tool.
FundCount
FundCount emphasizes accounting and fund administration in its product positioning. Its own comparison materials state the platform "is not positioned primarily as portfolio monitoring software," with strength in "accounting-backed portfolio accounting, performance measures, attribution, partnership accounting, reporting, document intelligence, and investor delivery" (FundCount vs Allvue). Buyers needing portfolio company KPI collection should test that workflow separately.
FundCount does offer document intelligence that extracts fields from capital calls, distributions, capital-account and co-investment statements, invoices and financial statements, including unstructured PDFs in formats it has not seen before. We did not find FundCount material on covenant compliance certificate ingestion or debt-schedule tracking for portfolio companies carrying debt.
Best for: firms prioritizing fund accounting and reporting continuity over specialized portfolio company data extraction.
Allvue
Allvue sells a broad enterprise suite that spans fund accounting, investor relations, and portfolio monitoring, marketing itself as alternative investment software for the full fund lifecycle. Allvue's site groups data collection with its Portfolio Monitoring product.
Allvue describes configurable KPI templates for portfolio company collection. Allvue's own demo describes a portal where each portfolio company fills out a configurable KPI template, backed by an Excel mapping wizard for less standardized inputs. A newer Document IQ layer extracts data from financials, loan notices, and credit agreements, and Allvue describes its document extraction as covering financials that borrowers, administrators, and portfolio companies deliver in inconsistent formats (Allvue).
Buyers should ask about implementation scope and timeline for the modules they need.
Best for: large firms that want one platform across fund accounting, investor relations, and portfolio monitoring.
What to look for in a data collection platform
Start with format handling, extraction, submission follow-up and source traceback. Then test the monitoring workflows your PE firm needs, including approvals, covenant visibility for debt-carrying companies and LP reporting.
Format flexibility. Portfolio companies send financials as PDFs, scanned statements, and spreadsheets with inconsistent layouts. A platform that only accepts formatted CSV or Excel templates pushes the reformatting work back onto your analysts, who then re-key numbers by hand. Ask the vendor to ingest a messy scanned statement during the demo, not a clean template.
Submission tracking and reminders. Someone has to know which portfolio companies have reported and which are late. Without automated tracking dashboards and reminder workflows, an analyst spends the quarter sending follow-up emails and chasing delinquent submissions manually. Confirm the platform tracks status per company and sends reminders without a human triggering each one.
Extraction versus template-based entry. Templates require someone to map information into predefined fields. Ask each vendor to extract figures from an unfamiliar document, show how your mapping decisions carry forward and identify what needs human review. Confirm which capabilities are generally available.
Auditability and source traceability. Ask each vendor to trace a dashboard figure to its source page and show the calculation rules carried forward. Check who reviews staged results, who can publish them and whether the system of record retains threshold and amendment history.
Conclusion
Lumonic is built around the one task this list measures. Portfolio companies send financials as PDFs, scanned statements, and spreadsheets that never match a template, and Lumonic reads those files directly, extracts the numbers, and maps them into structured fields without an analyst retyping anything. Automated reminders and a submission tracking dashboard chase delinquent companies so your team stops doing it by hand. Every extracted figure links back to the exact cell in the original document, so a reviewer can verify a number in seconds.
FAQs
How is PE data collection different from LP reporting software? PE data collection pulls financials and KPIs inbound from portfolio companies into a structured format. LP reporting sends fund performance outbound to investors. Lumonic handles the inbound collection job, extracting non-standardized submissions before that data ever reaches an LP report.
Is AI extraction reliable enough to replace manual entry? AI extraction reads source documents and pulls out numbers without manual re-keying. Lumonic pairs that extraction with source-cell traceability and human review of flagged exceptions rather than a black box. The result is handling of PDFs, Excel files, and scanned documents with every value staged for review and verifiable against its origin.
What does source-cell traceability mean in practice? Every extracted figure links back to the exact cell or line in the original document. Lumonic stores that link so an analyst can click a number in the dashboard and see its source. It prevents untraceable numbers and makes audit review fast instead of forensic.
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.
