Real estate private equity

Make good on your AI promise.

You told your LPs, your IC, or your board that AI is part of the strategy. We build the infrastructure that makes that true — connected to your actual data, governed for institutional use, and delivered by people who know how REPE works.

  • Yardi / MRI
  • Argus
  • Excel models
  • LP reporting
  • IC packs
  • Fund and asset reporting

The situation

The commitment is made. The infrastructure is missing.

Most REPE firms run on Yardi or MRI as the source and Excel as the integration layer. One analyst owns the model and the institutional memory behind it. When a parent company, an LP, or a new partner asks for standardized data, that analyst works the weekend. AI needs governed data, repeatable logic, and outputs the firm can defend.

The operating layer

AI operating layerReads your fund data, checks definitions against source records, drafts LP reports, and flags variances against data your team has approved.
human-approved

1. Source systems

  • Yardi / MRIFinancial and operating records
  • ArgusAsset-level underwriting and cash flows
  • Excel modelsAbsorbed into the record, not replaced
  • LP portalsCapital activity, notices, distributions
  • Third-party feedsMarket data, benchmarks, CoStar
Your data already lives somewhere.

2. Pipeline & integration

  • Pull from the systems where the work lives
  • ETL/ELT in Python and SQL
  • State, retries, and observability built in
Data moves reliably.
Owned end to end.

3. Data modeling & warehouse

  • Data warehouse design for fund, asset, and deal level
  • Modern lakehouse on Databricks, Snowflake, or Azure
  • Modeled around the questions your IC and LPs actually ask
Structured. Modeled.
Built for decisions.

4. Semantic layer & governance

  • Metrics & definitions
  • Waterfall logic
  • Access & security
  • Data quality
  • IRR means the same thing everywhere
  • Waterfall logic defined once, applied consistently
  • Lineage, validation, and audit trail
One definition.
Trusted by every team.

5. End users

  • PartnersFund-level view, IC-ready
  • Asset managersProperty-level, variance vs. budget
  • AnalystsSelf-serve with trusted data
  • LP reportingGenerated in hours, not assembled over days
  • AI agentsDraft, check, and execute against governed data
Trusted data.
Used by people and agents.
SourceIntegrateModelGovernDeliver

Control · continuity · auditability

Who this is for

The firm under new ownership

A parent company or institutional platform now expects standardized quarterly data. The existing stack was built for internal reporting. The gap shows up every quarter-end.

The firm that made the promise

Leadership told LPs or the board that AI is part of the strategy. The ops team or a senior analyst got the assignment. They need something real that survives a follow-up question.

The firm where one analyst owns everything

The model, the reporting, and the quarterly pack sit with one person. One departure creates risk. The goal is to make the work reproducible.

Proof

Built the layer

Mid-market REPE firm, approximately $3B AUM, 18-person team. Yardi and Excel were the starting point. We replaced analyst-built LP packs with a reporting layer that pulled directly from source systems. Quarterly IC memo prep went from two days to four hours. The firm passed an LP audit without material reconciliation issues.

Stayed in Excel

A larger shop was acquired by a global asset management platform. The analyst who owned the model left. The new hire could not reproduce it. An LP audit surfaced three inconsistencies across reporting periods. Remediation took two months. The parent company installed its own oversight layer.

The difference was infrastructure that existed outside one person’s workbook.

If your quarterly LP pack still lives in Excel, let’s talk.

In 30 minutes, we’ll map what you have, what you promised, and what it takes to close the gap.