Market Rent Refresh

Produces a decision-grade submarket brief that strips broker narratives to reveal what is actually happening in a market. IC-memo-ready output with no-fluff mandate, range-based forecasting, supply pipeline by quarter, demand drivers, competitive set, and 'What the Brokers Won't Tell You' section.

Transforms a tokenized/extracted rent roll into validated, typed, auditable, database-ready records: a multi-line charge schedule (base rent, CAM/tax/insurance recoveries, percentage rent, parking, storage) mapped to the canonical chart of accounts, lease- and unit-level facts, GPR and occupancy aggregates, a data-quality grade, and a target-model load plan. Tenant identity is pseudonymized; per-unit natural-person data never leaves the boundary. Triggers on 'load this rent roll into the database', 'normalize the rent roll to our schema', 'rent roll to warehouse', or when extracted rent-roll tokens need to become structured records before underwriting or tie-out.

Reconciles a normalized rent roll against a normalized T-12 on a stated, consistent basis (annualized contractual vs recognized accrual; collected cash out of scope) and never forces a tie. Reconciles base rent, recoveries and other income (jointly, per the canonical chart), occupancy, and the EGI / NOI-revenue bridge; classifies each gap as mapping, timing, or missing on a deterministic signature; surfaces residual_unexplained; and routes every untied dimension to human review. Triggers on 'tie out the rent roll to the T-12', 'reconcile contractual rent to actuals', 'NOI bridge from the rent roll', or 'revenue leakage check'.

Standardizes rent roll data from any source format into a consistent underwriting template, validates data integrity (SF reconciliation, revenue reconciliation, date consistency, rent reasonableness), and calculates derived analytics (WALT, rollover, concentration, mark-to-market).

Ingests raw rent rolls (pasted table, CSV, or PDF extract) and produces a clean dataset with layered analytics: rollover schedule, mark-to-market waterfall, tenant concentration risk, WALT, rent benchmarking, MTM exposure, and data quality flags. Triggers on 'analyze this rent roll', 'clean up this rent roll', or when rent roll data needs preprocessing before underwriting.

Quantitative rent optimization framework with loss-to-lease waterfall analysis, renewal probability modeling, effective rent NPV comparison across aggressive/moderate/retention strategies, valuation impact quantification, and market cycle overlay. Maximizes long-term property value, not just next-quarter revenue. Triggers on 'rent raise plan', 'rent optimization', 'loss-to-lease', 'renewal pricing', or when planning rent increases across a portfolio.

Generates structured CRE market research memos covering MSA, submarket, and sector-level conditions. Synthesizes supply/demand fundamentals, rent trends, cap rate movements, capital markets conditions, and forward-looking signals into investment-grade market commentary. Triggers on 'write a market memo', 'market update', 'submarket analysis', or when a user provides market data and asks for a written synthesis. Designed to feed the AMOS deal pipeline and supplement reit-profile-builder output.

Produces a comprehensive market cycle positioning report using the Mueller Real Estate Cycle model. Combines cycle timing analysis with capital markets intelligence (transaction volume, cap rate decomposition, capital flows, investor sentiment) to generate actionable buy/sell/hold recommendations across three time horizons.

Marketing material creation, broker event planning, TI cost benchmarking, marketing plan development, and commission structure benchmarking for Leasing Directors.

Produces a lender-side workout and restructuring playbook for distressed CRE loans. Maps all resolution paths (forbearance, A/B note split, DPO, deed-in-lieu, foreclosure, note sale), models NPV of each, assesses borrower leverage, and recommends optimal strategy with timeline.

Classifies work order urgency from free-text descriptions, assigns priority (P1-P4) with SLA deadlines, estimates cost, checks lease responsibility, and routes to the correct approval path.

Maps validated, warehouse-ready tabular datasets into deck-ready EXHIBIT specifications and slide inputs. Selects table vs. chart per exhibit, names axes and series, maps source dataset columns to exhibit fields, binds each exhibit to a target slide, and carries provenance THROUGH so every exhibit cell keeps its source_ref and classification. Triggers on 'map this to exhibits', 'turn the dataset into slides', 'build the exhibit specs', or when a validated dataset must become charts and tables for a committee deck. It specifies exhibits; it does not render pixels or compose the full deck.