Due Diligence
Normalize T-12s. Analyze rent rolls. Flag red flags. The manual data work of diligence — handled.
Due diligence is a data problem. Your team opens the data room, downloads dozens of documents, and starts the manual work — re-keying rent rolls, normalizing operating statements, cross-referencing lease abstracts against the OM. The analysis gets done, but half the time is data entry.
Upload the entire data room. Apers extracts, organizes, and cross-references every document — rent rolls standardized, T-12s normalized, lease abstracts mapped to operating data, discrepancies flagged with source citations. Your team focuses on judgment calls, not data entry.
Four Steps to Institutional Due Diligence
Upload the data room
Drag the full document set into the Data Room — OM, rent roll, T-12, title report, environmental, leases. Apers processes every file in parallel, extracting key terms and structuring data automatically.
Apers cross-references everything
Rent roll revenue reconciled against the T-12. Unit counts checked against the OM. Lease terms mapped to operating assumptions. Discrepancies flagged with source page citations.
Review flagged items
Each flag includes the conflicting values, the source documents, and a severity rating. Resolve items one at a time or delegate sub-chats to investigate specific issues in depth.
Export the checklist
The completed diligence checklist saves to Google Sheets with every item traced to source. Share with your IC or save to your Library as a template for the next deal.
Document Processing at Scale
Rent rolls, T-12s, lease abstracts, appraisals, environmental reports, title documents — extracted and structured automatically. No re-keying, no copy-paste, no missed pages.
Cross-Reference Everything
When the OM says 240 units but the rent roll lists 242, Apers flags it. Revenue reconciled across documents, expense line items validated, lease terms checked for consistency.
Nothing Missed
Institutional-grade due diligence checklists — environmental, legal, financial, physical — tracked to completion with gaps flagged automatically and severity ratings assigned.
Parallel Investigation Threads
Spin up sub-chats to investigate specific issues — title exceptions, environmental concerns, lease audits — each with full access to the Data Room but isolated from each other.
Audit-Ready Documentation
Every finding traced to source document and page number. Export the full diligence package to Google Sheets or save to your Library as a Playbook for future acquisitions.
Models
Frequently Asked Questions
How does Apers speed up due diligence?
Upload the entire data room. The UDPE engine extracts data from every document — rent rolls, T-12s, lease abstracts, environmental reports — normalizes formats, cross-references figures, and flags discrepancies with source citations. Your team focuses on judgment calls instead of data entry.
What types of documents can Apers process for due diligence?
Apers reads scanned PDFs, native PDFs, Excel files, Word documents, and even photos of physical documents. Common due diligence documents include OMs, rent rolls, T-12s, lease abstracts, phase I reports, surveys, and title documents.
How does Apers flag discrepancies during due diligence?
Apers cross-references data across documents — comparing rent roll figures to the OM, T-12 line items to the budget, and lease terms to the operating data. When figures do not match, Apers flags the discrepancy with citations to both source documents so you can investigate.
Can I run parallel diligence workstreams in Apers?
Yes. Open separate sub-chats for financial analysis, lease review, and market research. Each sub-chat has full access to the Data Room but is isolated from the others, so workstreams do not cross-contaminate. Export findings between threads to build a complete picture.
Is the due diligence output auditable?
Every value Apers extracts or calculates is traced to its source document in the Data Room. You can verify any figure by following the citation trail back to the original page and line item. Models open in Google Sheets with full version history.