Building the Intelligence Engine for Self-Storage
Real Estate
B2B
Artificial Development
Project Overview
Radius+, operated by Union Realtime LLC, aimed to establish itself as the definitive market-intelligence platform for the self-storage industry. Historically, investment and development decisions in this sector were hampered by fragmented data, manual spreadsheets, and slow, error-prone underwriting processes. Mindrind partnered with Radius+ to address these inefficiencies by designing and engineering a sophisticated artificial intelligence layer. This AI layer transforms raw, scattered market data into rapid, defensible decisions, providing self-storage professionals with a unified, AI-assisted view of any storage market.
The core of this engagement was the development of Cactus AI, an automated underwriting and document intelligence engine. This innovative system allows users to simply drag and drop deal packages such as rent rolls, broker offering memorandums, and operating statements. Within seconds, Cactus AI extracts critical financial data, enriches it with live Radius+ market intelligence, and generates a structured underwriting analysis complete with pre-populated metrics like gross rental income, expense ratios, and cap rates. What once consumed hours or days of an analystโs time is now accomplished in minutes.
Beyond Cactus AI, Mindrind significantly contributed to the broader data and intelligence infrastructure of the Radius+ suite. This included developing a daily unit-level pricing pipeline, the Radius Relay programmatic data integration for Excel, and comprehensive supply, demand, and feasibility analytics covering both U.S. and Canadian markets. These combined capabilities empower operators, investors, developers, lenders, and appraisers with unparalleled insights into self-storage markets.
Core Technologies
Challenges & Constraints
The self-storage industry faces an increasingly complex environment, with demand pressured by slower employment growth and softer home sales, while supply growth tightens due to financing and execution challenges. Performance has become highly market-specific, making fast, local intelligence more valuable yet more difficult to acquire. Before Mindrindโs AI engagement, the self-storage investment workflows were impeded by four significant structural problems:
Outdated Financial Underwriting
Reliance on manual spreadsheet modeling meant analysts spent countless hours rekeying figures from PDFs and offering memorandums. This process was not only slow and repetitive but also highly susceptible to transcription errors.
Unreliable and Fragmented Market Data
Essential pricing, supply, and demand signals were scattered across disconnected sources. Without a single, authoritative dataset, teams were forced to make high-stakes decisions based on stale, inconsistent, or unreliable inputs, increasing business risk.
Slow and Fragmented Deal Cycles
The journey from initial market research to issuing a letter of intent involved piecing together information from multiple tools and documents. Each handoff introduced delays, and in competitive markets, speed often dictates the success or failure of a deal.
Disconnected Tools
Market research, underwriting, and presentation tools existed in separate silos. This forced analysts to constantly switch between systems, creating workflow friction and reducing overall efficiency.
The fundamental issue was clear: while world-class market data existed, its conversion into a defensible underwriting decision still demanded slow, manual human effort. The strategic opportunity lay in bridging this gap with advanced AI.
Our Approach
Mindrindโs engagement with Radius+ followed a structured and iterative approach, ensuring that the AI components were robust, scalable, and delivered measurable value at each phase. Technical Approach & Architecture The platform was architected as a set of cooperating, distinct layers, each with a clearly defined responsibility. This modular design enhances maintainability and allows for independent evolution of the AI components from the core data backbone.
Technical Approach & Architecture
- Ingestion Layer: Responsible for collecting deal documents and continuously refreshed market feeds, normalizing formats, and queuing them for processing.
- Ingestion Layer: Responsible for collecting deal documents and continuously refreshed market feeds, normalizing formats, and queuing them for processing.
- Ingestion Layer: Responsible for collecting deal documents and continuously refreshed market feeds, normalizing formats, and queuing them for processing.
- Ingestion Layer: Responsible for collecting deal documents and continuously refreshed market feeds, normalizing formats, and queuing them for processing.
- Ingestion Layer: Responsible for collecting deal documents and continuously refreshed market feeds, normalizing formats, and queuing them for processing.
- Ingestion Layer: Responsible for collecting deal documents and continuously refreshed market feeds, normalizing formats, and queuing them for processing.
Results & Impact
By unifying comprehensive market data with AI-driven underwriting, Mindrind empowered Radius+ to move beyond being just a powerful data source to becoming an indispensable, end-to-end decision engine for the self-storage industry. The strategic impact on Radius+ and its users is profound
Historically, investment and development decisions in this sector were hampered by fragmented data, manual spreadsheets, and slow, error-prone underwriting processes.
Mindrind partnered with Radius+ to address these inefficiencies by designing and engineering a sophisticated artificial intelligence layer.
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Before
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
After
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
- Manual spreadsheet-based underwriting
What Our Client Says About Us
Mindrind helped us transform Radius+ from a market-data platform into a true AI-powered decision engine. With Cactus AI, our users can move from raw deal documents to defensible underwriting insights in minutes instead of hours or days.
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