AI Automation Blog
Discover the latest trends, strategies, and best practices for implementing AI automation in your business. From agent building to infrastructure optimization.
Showing 18 of 302 articles
How to Abstract a Commercial Lease with AI
How to Abstract a Commercial Lease with AI
How to abstract a commercial lease with AI: ingest the full stack, extract economic and legal terms with clauses cited, normalize, and flag the gaps.
How to Build a Submarket Intelligence Report with AI
How to Build a Submarket Intelligence Report with AI
How to build a submarket intelligence report with AI: sourced fundamentals, normalized comps, labeled forward signals, and a thesis your IC can act on.
NYC Multifamily Off-Market Sourcing: Debt Signals
NYC Multifamily Off-Market Sourcing: Debt Signals
How to source off-market multifamily in Brooklyn and Queens by reading debt and loan-maturity signals from NYC public records. A methodology piece on the honest maturity denominator, from a representative multi-submarket study of roughly 19,500 properties and 356,000 units.
The Most Concentrated US Commercial Real Estate Markets
The Most Concentrated US Commercial Real Estate Markets
In some US counties the top 10 owners hold nearly a third of all commercial parcels. In others, no owner controls even 2%. Here is where commercial real estate is concentrated, and what it means for sourcing.
US Off-Market Commercial Real Estate by the Numbers (2026)
US Off-Market Commercial Real Estate by the Numbers (2026)
We mapped 3.48M commercial parcels across 261 counties in 44 states from public records. Here is the national picture: the biggest markets, the asset mix, and the honest coverage story.
Where US Off-Market Commercial Real Estate Owners Are Reachable
Where US Off-Market Commercial Real Estate Owners Are Reachable
Of 261 US counties we mapped, owner records are broadly accessible in public record in 191 and limited in 70. Here is the honest map of where you can reach commercial owners, and where sourcing gets hard.
How to Produce Broker Opinions of Value (BOVs) at Scale with AI
How to Produce Broker Opinions of Value (BOVs) at Scale with AI
A five-step pipeline to produce broker opinions of value with AI: standardize inputs, pull sourced comps, run valuation scenarios, and sign it yourself.
How GPs Use AI to Run the Capital Raise
How GPs Use AI to Run the Capital Raise
How GPs use AI across the capital raise: match investors, draft the memo from underwriting, answer data-room Q&A, chase sub-docs, and draft LP updates.
AI for Commercial Real Estate by Asset Class
AI for Commercial Real Estate by Asset Class
The AI playbook for commercial real estate is not one playbook. It changes by asset class because the data sources, the buy signals, and the underwriting math are different for multifamily than they are for self-storage or hotels. This is the map: what is specific to each asset class, and what stays constant no matter what you invest in.
AI for Hotel and Hospitality Real Estate Investing
AI for Hotel and Hospitality Real Estate Investing
Hotels are the one commercial real estate asset class where you are underwriting an operating business, not just a building. AI earns its keep here parsing STR reports and monthly operating statements, benchmarking RevPAR and ADR against a comp set automatically, and flagging brand and franchise terms buried in management agreements, work that used to take an analyst days per property.
AI for Industrial Commercial Real Estate (Warehouse, Logistics, IOS)
AI for Industrial Commercial Real Estate (Warehouse, Logistics, IOS)
AI helps industrial CRE investors find off-market warehouse, distribution, and industrial outdoor storage (IOS) deals faster, and underwrite them with clear-height, dock-door, tenant-credit, and rollover data pulled automatically instead of assembled by hand.
AI for Manufactured Housing and Mobile Home Park Investing
AI for Manufactured Housing and Mobile Home Park Investing
Manufactured housing community investors use AI for three things: finding off-market parks in a fragmented ownership base, underwriting lot-level economics fast, and keeping pipeline moving without adding headcount. Here is what is actually different about MHC and where AI fits.
AI for Multifamily Investing: Sourcing, Underwriting, Operations
AI for Multifamily Investing: Sourcing, Underwriting, Operations
AI helps multifamily investors move faster across the full deal lifecycle: finding off-market opportunities earlier, standardizing rent rolls and T-12s into a first-pass underwriting model in minutes instead of days, and flagging distress signals before a listing goes live. The gain is time and coverage, not a replacement for underwriting judgment.
AI for Retail Commercial Real Estate: Shopping Centers and Net Lease
AI for Retail Commercial Real Estate: Shopping Centers and Net Lease
AI helps retail CRE investors abstract co-tenancy clauses and percentage rent out of leases, flag tenant health risk before a default hits the P&L, and underwrite shopping centers and net lease deals faster by pulling rollover schedules, sales-per-square-foot, and trade-area demographics into one model.
AI for Self-Storage Investing: Sourcing, Underwriting, Revenue
AI for Self-Storage Investing: Sourcing, Underwriting, Revenue
AI helps self-storage investors find off-market single-facility deals before they hit LoopNet, underwrite unit-mix and rate-management assumptions faster, and run existing-customer rate increases without a revenue-management platform contract. The edge shows up in three places: sourcing fragmented owners, tightening the physical-to-economic occupancy math, and keeping street rates and in-place rents in sync.
Claude Code for Commercial Real Estate Teams
Claude Code for Commercial Real Estate Teams
Claude Code is an agentic coding tool: you describe what you need in plain English and it writes, tests, and runs real software in your own environment. For a CRE firm, that means custom underwriting tools, data pipelines, and internal systems built to your workflow, not a vendor's roadmap, and owned by you when it ships.
Claude for Commercial Real Estate: Models, Skills, and Workflows
Claude for Commercial Real Estate: Models, Skills, and Workflows
Claude is Anthropic's family of AI models, and CRE firms use it because it holds an entire offering memorandum, rent roll, or lease in one pass and reasons carefully instead of guessing. This is the hub for how CRE teams actually put Claude to work: the model family, the skills, the workflows, and when to build it yourself versus bring in a partner.
Using Claude Projects for CRE Deal Work
Using Claude Projects for CRE Deal Work
Claude Projects is a persistent workspace that holds your files, instructions, and context across chats, which makes it a solid free starting point for CRE deal work: load your buy-box, underwriting template, and IC-memo format once, then reuse them on every OM instead of re-explaining your standards each session. It is not a system of record and it does not automate anything or connect to your data room, CRM, or email, so it works well for a single analyst's individual deals and breaks down once a team needs shared history, integrations, or an audit trail.
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