The World Is Selling Prompts.
We Built the Intelligence.

General AI with Prompts

• ✗Requires complex, expert-crafted prompts to get useful output
• ✗Hallucinates cap rates, NOI figures, and market data
• ✗No understanding of C-PACE, tax credit stacks, or adaptive reuse
• ✗Cannot evaluate a construction budget or draw schedule
• ✗Treats a T-12 like a spreadsheet, not a financial story
• ✗Sold by people who have never underwritten a deal

BCA Data Intelligence

• ✓No prompting required — the model understands real estate natively
• ✓Trained on billions in real institutional deal decisions
• ✓Full C-PACE, tax credit, and adaptive reuse modeling data
• ✓Construction cost, permit history, and draw schedule intelligence
• ✓Go/No-Go labels with full underwriting context attached
• ✓Built by analysts who have done this at the highest levels

Commercial transaction data cleaned, geocoded, and structured for machine learning ingestion — not for human analysts. Every record is normalized to a consistent schema across asset class, geography, and deal type. Delivered in Parquet, JSONL, or structured CSV. Built from live market data processed through BCA's institutional underwriting framework.

• —Sale price, cap rate, buyer/seller entities, financing terms
• —Asset class: multifamily, industrial, retail, office, mixed-use, data center
• —Geographic filtering by MSA, submarket, or custom radius
• —Linked to permit history, rent rolls, and operating statements where available
• —Formatted for LLM ingestion and neural network training pipelines

The rarest asset in real estate AI: expert-labeled deal decisions with full underwriting context attached. Each record contains the deal parameters, the financial model output, the capital stack structure, and the final Go/No-Go determination — made by analysts who have underwritten billions of dollars at the highest institutional levels. This is what separates a model that predicts from one that understands.

• —Deal parameters: purchase price, rehab budget, ARV, NOI, DSCR
• —Capital stack: senior debt, mezzanine, equity, C-PACE, tax credits
• —Go/No-Go label with annotated reasoning
• —Stress-tested scenarios at multiple vacancy and cost assumptions
• —Construction feasibility and absorption analysis included

Building permit histories, contractor data, material cost benchmarks, renovation ROI outcomes, and adaptive reuse feasibility data — structured for construction cost estimation AI, renovation ROI prediction models, and C-PACE prep modeling. The data that trains AI to evaluate a construction budget the way an experienced developer does.

• —Permit histories linked to transaction records and ownership data
• —Hard cost benchmarks by asset class, geography, and construction type
• —Adaptive reuse feasibility indicators and conversion cost histories
• —C-PACE eligibility data and energy retrofit cost structures
• —Draw schedule modeling data for ground-up construction AI

Structured datasets for training AI on the most complex real estate financing scenarios: C-PACE integration, state and federal tax credit modeling within the debt/equity stack, Historic Tax Credit (HTC) and Low-Income Housing Tax Credit (LIHTC) structures, and credit monetization strategies. This is the data that trains AI to handle what general-purpose models hallucinate on.

• —C-PACE financing structures and eligible improvement cost data
• —Federal and state tax credit stacks: HTC, LIHTC, NMTCs
• —Credit sale and monetization transaction histories
• —Debt/equity waterfall structures across deal types
• —IRR and yield analysis across capital stack configurations

Private Equity & Institutional Funds

Train internal underwriting AI on institutional-grade labeled deal data — not legacy schema from data aggregators that was never designed for machine learning.

Hard Money & Private Lenders

Stop approving borrowers. Start approving deals. Build the AI that evaluates construction budgets, absorption, and capital stacks — not just credit scores.

PropTech & AI Startups

Skip the data engineering bottleneck. Get structured, ML-ready real estate datasets delivered in the exact format your pipeline needs — without building the collection infrastructure yourself.

Commercial Brokers & Platforms

Give your clients AI-powered comp analysis and deal intelligence trained on real transaction outcomes — not statistical averages from public records.

Define Your Use Case

Tell us what your AI needs to do — underwriting, valuation, construction cost estimation, capital stack modeling, or something more specific. We scope the exact dataset your model needs.

Custom Data Engineering

We build the dataset using BCA's institutional underwriting framework and live market data. Every record is cleaned, structured, labeled, and formatted for your specific ML pipeline.

Delivery & Integration

Delivered in your preferred format — Parquet, JSONL, structured CSV, or API-ready JSON. We provide schema documentation and can support integration into your training pipeline.

Ongoing Data Partnership

Real estate markets move. We offer ongoing data refresh subscriptions and custom data engineering retainers for firms that need live, continuously updated training data.