Make smarter CRE investments with AI-powered analytics that analyze market trends, underwrite deals, optimize portfolios, and identify opportunities across office, retail, industrial, and multi-family assets.
CRE investors and operators rely on outdated tools, manual analysis, and lagging data. Without AI-powered analytics, firms miss opportunities and make suboptimal decisions:
CRE data scattered across CoStar, REIS, LoopNet, local brokers, and internal systems. Analysts spend 60% of time aggregating data instead of generating insights.
Deal analysis takes days or weeks. Spreadsheet-based models are error-prone and inconsistent. Fast-moving opportunities are lost to competitors with better tools.
Teams can only actively monitor 10-20 markets. AI can analyze hundreds of markets simultaneously to surface emerging opportunities before they're obvious.
Quarterly reviews and static analysis miss trends. Real-time AI monitoring identifies underperforming assets, market shifts, and optimization opportunities continuously.
We build unified analytics platforms that aggregate CRE data, automate underwriting, predict market trends, and optimize portfolios with machine learning.
We integrate data from CoStar, REIS, RCA, PropertyShark, public records, and proprietary sources into a unified data warehouse.
We deploy ML models that analyze supply/demand, predict rent growth, forecast cap rates, and identify market inflection points.
We build intelligent underwriting engines that automate rent comps, expense benchmarking, cash flow modeling, and return projections.
We deploy AI systems that monitor portfolio performance, identify value-add opportunities, and optimize allocation across markets and property types.
We build AI systems that screen thousands of properties, rank opportunities, predict off-market deal likelihood, and identify value-add strategies.
Request a demo using your actual portfolio data and investment criteria.
Each CRE asset class requires specialized analytics tailored to its unique drivers and metrics:
ML models analyze tenant credit quality, lease expiration schedules, WFH adoption rates, and flight-to-quality trends. Predict future occupancy and rental rate trajectories in post-pandemic markets.
Geolocation data, mobile foot traffic analytics, and e-commerce penetration models predict retail performance. Identify experiential retail and last-mile fulfillment opportunities.
AI analyzes port volumes, inventory-to-sales ratios, e-commerce growth, and last-mile delivery needs. Predict warehouse demand and identify logistics hub opportunities.
Population migration, household formation, income trends, and new supply pipelines drive multi-family performance. ML models forecast rent growth and identify supply-constrained markets.
Analyze booking patterns, tourism trends, business travel recovery, and event calendars. AI-powered RevPAR forecasting and dynamic pricing optimization.
Track cloud provider expansion, AI/ML compute demand, and power availability. Predict colocation demand and identify markets with power and fiber infrastructure.
AI analytics combine traditional CRE data with alternative signals for superior insights:
Mobile device location data reveals retail traffic patterns, office occupancy, and mixed-use activity. Predict tenant sales and asset performance.
Track construction progress, parking lot occupancy, roof condition, and land use changes. Automate property inspections and verify development timelines.
Retailer sales data and spending patterns predict tenant health and rental income sustainability. Early warning signals for tenant distress.
Monitor broker listings, tenant reviews, permit filings, and local news. NLP extracts market sentiment and identifies emerging trends.
Manage multi-billion dollar portfolios with AI-powered analytics. Real-time performance monitoring, predictive maintenance, and portfolio optimization across hundreds of assets.
Screen deal flow efficiently and identify value-add opportunities. AI underwriting accelerates due diligence and improves bid-ask price accuracy.
Forecast absorption rates, optimize unit mix, and time market entry. Predictive analytics reduce development risk and improve pro forma accuracy.
Automate loan underwriting and ongoing portfolio monitoring. Predict default probability and proactively manage credit risk across commercial mortgage portfolios.
Provide clients with data-driven market insights and property valuations. AI-powered analysis differentiates services and wins mandates from sophisticated clients.
Pros: Immediate access to standardized data and basic analytics. Cons: Generic insights, limited customization, no competitive differentiation. Best for smaller firms with standard needs.
Pros: Tailored to investment strategy, proprietary insights, competitive advantage, control over data. Cons: Higher upfront cost, 6-12 month build time. Best for institutional investors managing $500M+ AUM.
Use standard platforms for base data, add custom AI layers for proprietary analytics. Best balance of speed-to-market and differentiation for most firms.
Consider custom development if: (1) portfolio exceeds $500M, (2) specialized strategy requires unique analytics, (3) data integration complexity is high, or (4) competitive advantage depends on superior intelligence.
Reduction in underwriting time from days to hours
Improvement in return predictions vs. traditional pro formas
More markets analyzed per analyst with AI automation
Core: CoStar/REIS subscription, internal transaction data, portfolio performance data. Enhanced: Alternative data (foot traffic, satellite imagery), web scraping, public records. We can work with whatever data you have and supplement gaps.
Short-term (6-12 months): 80-85% directional accuracy for rent and occupancy trends. Long-term (3-5 years): Less precise due to compounding uncertainty, but superior to static assumptions. Best used for scenario planning and relative market ranking.
No. AI augments analysts by automating data aggregation and initial screening, allowing experts to focus on judgment-intensive tasks like strategy, negotiation, and relationship management. Think "analyst productivity multiplier" not replacement.
Development: 6-12 months. Payback: 12-24 months for institutional portfolios ($500M+). ROI comes from faster deal screening, better underwriting accuracy, avoided bad investments, and improved portfolio performance.
We implement strict data governance: on-premise or private cloud deployment, encryption at rest and in transit, role-based access controls, and NDAs. Your proprietary data never leaves your environment or mixes with other clients.
Analyze more markets, underwrite deals faster, and make better investment decisions with AI-powered commercial real estate analytics. Schedule a consultation to discuss your portfolio and requirements.
Related: AI Property Valuation | Market Prediction