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FORENSIC INTELLIGENCE FOR INSTITUTIONAL REAL ESTATE

A dataroom of binders and printed documents on a table
A desk with two monitors
Coverage monitor listing synthetic private real estate funds
A recorded finding with its evidence chain

Analyzing a property fund portfolio used to look like this

It looks like this now

Coverage, private fundsScan, coherence testing

Real estate does not lack information. It lacks a reliable way to reconstruct it.

An institutional portfolio is held through layers of entities, in several jurisdictions, under separate financing agreements. What it reports and what its own documents support are two different objects.

Reconciling them is manual, slow, and dependent on who does the work. Structural contradictions rarely appear inside one document. They emerge across them.

A contradiction that reaches the investment committee is a different problem from the same contradiction found in the record before it does. Every fact in a finding carries the document and clause it was read from, and every computed figure carries the facts behind it.

“One of the key issues faced by real estate companies is the unstructured labyrinth of real estate data.”

CBRE, How can AI bridge the gap for real estate investment managers? 2024

How a scan runs.

VDR, as delivered

  1. 01

    Ingestion

    Ingestion pipeline

    The raw data room enters as delivered, classified and normalised.

  2. 02

    Extraction

    LLM-assisted

    Facts extracted under a fixed schema, with the source of every value recorded.

  3. 03

    Structure reconstruction

    Deterministic

    Entity, debt, temporal and income layers rebuilt in pure code, independent of the reported figures.

  4. 04

    Coherence testing

    Deterministic

    Tests check whether the reconstructed structures can all be true at once.

  5. 05

    Delta computation

    Deterministic

    Reconstructed values compared to reported ones, as a quantified delta.

  6. 06

    Findings

    Deterministic

    Each finding carries a complete evidence chain to specific clauses.

When two documents cannot both be true, ReActive shows you where.

One finding, traced to its sources.

Recorded run log
  1. 09:12:07IngestionIngestion pipeline
  2. 09:38:20ExtractionLLM-assisted
  3. 09:41:02Structure reconstructionDeterministic
  4. 09:43:07Coherence testingDeterministic
  5. 09:44:19Delta computationDeterministic
  6. 09:45:02Findings identifiedDeterministic

Finding NTH-001   Surfaced structural exception

The planned exit window and the tenant break schedule fall in the same period

Model assumption

Disposal planned for H1 2027 at a 7.5% exit cap rate. The exit window is board confirmed; the cap rate is model sourced and is not board confirmed.

Assumptions Snapshot, Dec 2025   Board Meeting Minutes, Feb 2025

Documented reality

Break options across five tenancies fall inside that same window, exposing £2,846,924 of contracted rent to early exit.

Rent Roll, Dec 2024

Quantified delta

Break-exposed rent£2,846,924
Total contracted rent£10,568,623
Exposed share of contracted rent5 of 16 dated break options inside the window26.9%

Evidence chain

  • Rent roll, break scheduleNorthGate_Tenant_Schedule_Rent_Roll_Dec2024.pdf
  • Board-confirmed exit windowBoard_Meeting_Minutes_Feb2025.pdf
  • Model exit assumptionNorthGate_Financial_Model_Assumptions_Snapshot_Dec2025.pdf

Every displayed value traces back to the source document it was extracted from.

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Synthetic dataset representative of institutional real-estate operating conditions.

Origin

It started in 2009, rebuilding a listed property group from its own documents. The same reading has run through every situation since. ReActive is that method, made systematic.

ReActive Founder

EUR 2.4bnPortfolio reported
43%NAV delta
EUR 202mAbsolute delta

Documented months ahead of the market.

Read the origin

See a scan replayed.

The demo replays a recorded scan over a synthetic dataroom, from the documents to the findings.

contact@reactive-intel.com