Building the Intelligence Engine for Self-Storage
Self-Storage
Radius+
AI Product Design & ML Engineering
Project Overview
Radius+ aimed to be the definitive market-intelligence platform for the self-storage industry, a sector historically plagued by fragmented data, manual spreadsheets, and slow underwriting. Mindrind partnered with Radius+ (Union Realtime LLC) to engineer the AI layer that transforms scattered market data into fast, defensible investment decisions.
The core of this engagement is Cactus AI, an automated underwriting and document-intelligence engine. It allows users to drag and drop deal packages like rent rolls and operating statements and within seconds, the system extracts financials, enriches them with live Radius+ market data, and produces a structured underwriting analysis with metrics such as gross rental income and cap rates. This compresses analysis from hours or days to minutes.
Beyond Cactus AI, Mindrind engineered the data and intelligence backbone powering the broader Radius+ ecosystem. This included developing a daily unit-level pricing pipeline that continuously monitors market pricing, building the Radius Relay Excel integration for seamless financial modeling and creating advanced analytics covering supply, demand, feasibility, demographics, and competitive market intelligence across the United States and Canada. By consolidating millions of data points into a unified platform, Mindrind enabled Radius+ users to access real-time insights, compare markets with confidence, automate underwriting workflows, identify investment opportunities faster and make data-driven decisions through a single AI-assisted source of truth for the self-storage industry.
Core Technologies
Challenges & Constraints
The self-storage industry faced a complex environment where investment and development decisions were hampered by outdated, manual workflows. Before Mindrindโs AI engagement, four structural problems significantly slowed down critical investment processes:
Outdated, Manual Financial Underwriting
Underwriting relied on tedious, manual spreadsheet modeling. Analysts re-keyed figures from PDFs, a slow, repetitive process prone to transcription errors that compounded through pro- forma analyses.
Unreliable & Fragmented Market Data
Key pricing, supply, and demand signals were siloed in disconnected sources. This fragmentation forced high- stakes decisions to be made on stale, inconsistent, or unreliable data inputs.
Slow & Fragmented Deal Cycles
The journey from initial market research to a letter of intent involved stitching together multiple tools and documents. Every handoff added time, increased operational complexity, and speed was often critical for winning deals.
Disconnected Tools & Workflows
Market research, underwriting and presentation existed in separate systems. This forced analysts out of their preferred workflows, creating significant friction at every step of the deal process, reducing efficiency and increasing manual coordination between teams.
The Fundamental Issue Was Clear: World-class market data existed, but converting it into a defensible underwriting decision was slow, manual, and human-intensive. The strategic opportunity was to close that gap with AI.
Our Approach
Mindrind designed a layered intelligence architecture for Radius+ that ingests raw data, applies machine learning for structuring, enriches it with proprietary market intelligence, and delivers results within usersโ trusted workflows. The core principle was to remove manual, repetitive work so human expertise could focus on judgment, not data entry.
Technical Approach & Architecture
- Ingestion Layer: Collects deal documents and continuous market feeds, normalizing formats for processing.
- Document Intelligence: Uses OCR, LLM, and entity recognition to read unstructured PDFs and extract structured financial fields.
- Data Normalization & Validation: Reconciles extracted values against a canonical schema, validates ranges, and flags low-confidence fields.
- Enrichment & Analytics: Joins extracted deal data with Radius+ market data to compute underwriting metrics and supply/demand indicators.
- Underwriting Engine: Runs pro-forma and scenario calculations across various purchase prices to surface profitability.
- Delivery & Integration: Provides web application, one-click presentation generation, LOI export, and the Radius Relay Excel plug-in.
- AI Decision Support Layer: Applies AI-powered reasoning and business rules to highlight investment risks, surface key opportunities, and generate actionable insights for faster decision-making.
- Reporting & Visualization: Transforms underwriting outputs into interactive dashboards, executive reports, and presentation-ready visualizations, enabling stakeholders to review opportunities quickly and collaborate more effectively.
Results & Impact
By unifying market data with AI-driven underwriting, Mindrindโs platform for Radius+ fundamentally transformed how self-storage professionals make decisions. The solution compressed deal analysis from days to minutes, significantly reducing manual data entry and accelerating deal cycles.
Radius+ evolved from being a powerful market data provider into a comprehensive, AI-powered decision intelligence platform. Operators, investors, brokers, lenders, and asset managers gained access to a unified ecosystem for market research, pricing intelligence, automated underwriting, financial modeling, and investment analysis. By combining intelligent automation with trusted market data, the platform empowered users to make faster, more defensible investment decisions, improve operational efficiency, and scale acquisition workflows across self-storage markets throughout the United States and Canada.
Messages delivered securely to lawmakers
Across web and mobile
and 60% faster AI message generation
Improvement in data scalability and accuracy.
Eliminating manual rekeying from PDFs and memos.
Underwriting Key metrics populate automatically from live data.
Before
- Manual, Spreadsheet-Based Financial Underwriting
- Fragmented Pricing, Supply, and Demand Data Sources
- Multi-Day Deal Cycles from Research to LOI
- Disconnected Tools for Market Research and Presentations
- High Potential for Manual Data Entry and Modeling Errors
After
- AI-Driven Document Extraction & Automated Underwriting
- Unified, Real-Time Market Data Across All Analysis
- Compressed Deal Cycles to Same-Session Workflows
- Integrated Platform, Including Excel Plug-in (Radius Relay)
- Source-Based, Enriched Metrics for High-Confidence Decision
What Our Client Says About Us
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"Mindrind became a true extension of our product and engineering team. Their AI expertise helped us transform complex underwriting, market intelligence, and document processing into a seamless platform that delivers real value to operators, investors, and lenders."