These tutorials, workshops, and case studies show how CRE teams run real deals with AI — from sourcing through investor updates. Start with Featured for the most reusable patterns.
A CRE comps platform packaging AI search, predictions, and summaries around real lease and sale data.
A curated set of reusable Lev Agent prompts with use cases and public launch links for common CRE workflows.
A useful enterprise benchmark for how a large CRE organization packages and explains a domain-tuned AI experience.
A practical guide to structuring Claude-based workflows for CRE deal teams, from knowledge organization to repeatable execution.
A workshop and education hub for commercial real estate teams exploring AI-powered legal, deal, and operations workflows.
A concise ladder for moving a real estate team from casual AI experiments to repeatable operating practices.
A practical piece on the data quality and governance work needed before enterprise AI in CRE can succeed.
Launch context for CompStak AI, including the kinds of market-analysis and search workflows it supports.
A useful product writeup for understanding what strong CRE document extraction UX looks like in a live deal pipeline.
A product hub for AI-assisted deal creation, search, and extraction in institutional real estate workflows.
A role-based example of how a large CRE platform packages assistants for research, sales support, and operations.
A practical episode on applying AI to underwriting and marketing tasks in CRE.
A brokerage-authored blueprint for decomposing CRE tasks into Claude-powered agents and reusable operating patterns.
A write-up explaining the acquisition orchestrator architecture and why its multi-agent design matters for CRE builders.
A workshop page focused on operational automation patterns in multifamily property management.
A useful argument for why domain-specific and custom AI implementations matter more than generic chatbots in CRE.