Autonomous CRE Infrastructure
Pinchfin is an autonomous CRE credit operating system built on Claude Code. 28 domain-specific agents execute deterministic loan sizing, market research, comparable analysis, sponsor due diligence, and committee-grade document production across four institutional lending products — transitional bridge debt, construction loans, preferred equity, and sponsor acquisitions. Every calculation uses standardized CRE formulas in Python. Every analysis is sourced to verified data. Inbound submission to 8-document deal book in under 60 minutes.
5
Agentic workflows
330+
Skills
25
Live data feeds
28
Domain-specific agents
Platform
Core Analytical Framework
Deterministic calculations and artificial inference organized into 28 domain-specific agents — each with its own skills, credit methodology, and analytical scope.
Deterministic Calculations
Six-constraint loan sizing, DSCR, debt yield, LTV, IRR/MOIC, interest reserve shortfall, and sensitivity analysis — all calculated with standardized CRE formulas in Python. No AI in the math. Same inputs always produce the same output. Every formula, every input, every result is documented.
Risk Controls & Credit Gates
Three-tier credit review (Producer/Reviewer/Resolver), red flag detection, nuance gates, and deterministic validation — layered controls that catch errors, inconsistencies, and assumption drift before they reach the credit decision.
Committee-Grade Documentation
Artificial inference translates analysis directly into credit memoranda, presentation packages, diligence checklists, and reporting deliverables formatted for committee review.
Workflows
Five Agentic Workflows
End-to-end agentic workflows from deal intake through credit decision. Multiple domain-specific agents chain together — each executing its own skills within its own analytical scope — to produce committee-grade output autonomously.
Transitional Lending
Screen inbound deals, size senior debt, stress-test structure, frame credit risk, and carry the analytical file through committee presentation and into portfolio monitoring.
Construction Lending
Validate construction budgets, control draw schedules, monitor cost-to-complete exposure, and maintain completion visibility through the execution period.
Preferred Equity
Model combined capital structures, size preferred positions, evaluate intercreditor pressure points, and stress-test return protection under downside scenarios.
Sponsor Acquisition
Support rapid acquisition screening, enforce max-bid discipline, model renovation economics, and produce lender-ready execution packages at each stage.
Quick Review
Rapid 10-phase screening pass for every inbound deal: six-constraint sizing, preliminary credit metrics, market snapshot, sponsor profile, and 1-page screening memo with pass/watch/decline recommendation.
Users
Four User Perspectives
A single credit methodology with tailored output, terminology, and formatting for each counterparty.
Lenders
Designed for bridge lenders, debt funds, bank CRE desks, and balance-sheet originators — your credit methodology, enforced consistently from deal screen through credit approval and post-close portfolio monitoring.
Brokers
Built for mortgage brokers, debt advisors, and capital intermediaries — your market expertise, documented with rigorous analysis, sizing, and deal packaging.
Sponsors
Purpose-built for operators, developers, and equity sponsors — your acquisition thesis, stress-tested against the same constraints lenders apply, with committee-ready LP and lender deliverables.
Affordable Developers
Purpose-built for LIHTC developers, Section 8 operators, nonprofit housing organizations, and mixed-income developers navigating layered capital structures with regulatory compliance requirements.
Infrastructure
Shared Services
Five shared agents active across every agentic workflow, every user type, and every deal — from quick review through portfolio surveillance.
Deterministic Calculations
Every loan size, coverage ratio, return metric, and sensitivity output is calculated with full show-your-work transparency. Six-constraint waterfall, month-by-month interest reserve shortfall, dual-scenario cash flow — the formula, the inputs, the output. Same inputs always produce the same answer. All calculations use standardized CRE formulas in Python — deterministic, repeatable, and independent of AI inference.
Comparable Analysis Agent
Every rent assumption and value conclusion is derived from independently sourced market comparables. 5-7 rent comps, 5-7 sales comps with adjustment grids, market rent conclusion with confidence interval. Comparable database with 90-day rent / 180-day sales shelf life — each deal enriches the comp set for subsequent analysis.
Three-Tier Credit Review
Producer executes, Reviewer audits, Resolver decides. Three-tier governance on every critical analytical phase with structured escalation hierarchy. Independent audit before any deliverable ships — calculation accuracy, source verification, format compliance.
Nuance Gate Agent
Specialized analytical routing for rent control, LIHTC, ground lease, tax abatement, seismic, environmental, and complex ownership structures. Gate-keeping nuances trigger early GO/NO-GO decisions; contained nuances route to purpose-built methodology in their respective phases.
Document Review & Compliance Agent
First-pass review of all transaction documents — loan agreements, entity documents, borrower structures, PSAs, leases, third-party reports, regulatory agreements, and closing deliverables. Key term extraction, covenant identification, structural comparison against approved terms, and compliance verification using in-house counsel review standards. Not a substitute for legal counsel. All documents are subject to final legal review.
FAQ
Frequently Asked Questions
What is autonomous CRE underwriting?
Autonomous CRE underwriting uses multi-agent AI systems to independently analyze commercial real estate deals — from rent comps and market research to credit sizing and committee documentation — without human intervention at each step. Pinchfin's 28 domain-specific agents execute the full analytical workflow end-to-end, producing an 8-document deal book in under 60 minutes. Traditional manual underwriting takes 2-5 business days for the same output.
How does AI loan sizing work?
Pinchfin's loan sizing uses deterministic Python formulas to calculate the maximum loan amount. A six-constraint waterfall tests LTV As-Is, LTV Stabilized, DSCR Stabilized, Debt Yield Stabilized, Loan-to-Cost, and program cap simultaneously. The most restrictive constraint governs. Same inputs always produce the same output. Every formula, input, and result is documented with full calculation transparency.
What is an agentic AI workflow in commercial real estate?
An agentic AI workflow chains multiple domain-specific AI agents together, each executing its own analytical skills within its own scope. In Pinchfin, the transitional lending workflow runs 17 phases with 4 blocking gates — sponsor analysis, market research, comparable analysis, rent underwriting, expense normalization, cash flow construction, loan sizing, risk assessment, and credit decision — each phase producing verifiable output before the next begins. Unlike AI copilots that assist at individual tasks, agentic systems execute the complete workflow autonomously.
Is AI accurate enough for institutional CRE credit decisions?
Pinchfin separates deterministic calculations from AI inference. All loan sizing, DSCR, debt yield, LTV, IRR/MOIC, interest reserve sizing, and sensitivity analysis use standardized CRE formulas in Python — no AI in the math. AI inference handles research synthesis, narrative generation, and document production. A three-tier credit review (Producer/Reviewer/Resolver) audits every critical phase. Four blocking gates enforce upstream validation. 23 of 27 production runs have achieved 90%+ accuracy versus institutional benchmarks.
What CRE deal types does Pinchfin cover?
Five agentic workflows: (1) Transitional bridge lending for value-add multifamily, mixed-use, and lease-up; (2) Construction lending for ground-up and substantial rehabilitation; (3) Preferred equity with two-pass waterfall and PIK modeling; (4) Sponsor acquisitions with max-bid discipline and renovation economics; (5) Quick review for 10-minute pipeline triage. Deal range: $10M-$100M. Property types: multifamily, mixed-use, value-add, lease-up, ground-up construction, affordable/LIHTC.
How does Pinchfin handle LIHTC and affordable housing?
Full affordable housing module: LIHTC 4% and 9% credit calculation with QCT/DDA 130% basis boost, AMI-based rent ceiling modeling at 30/50/60/80% tiers, income averaging per Revenue Procedure 2022-14, layered capital structuring (tax credit equity + soft debt + conventional + gap funding), Section 8 and PBRA contract analysis, and state-specific QAP scoring intelligence. Live HUD data feeds provide current AMI limits and QCT/DDA eligibility status.