AI-Driven Market & Portfolio Insights: Extract actionable intelligence from unstructured data sources to enhance deal-making and portfolio management.
Automated Document Processing: Streamline CRE workflows by processing contracts, lease agreements, and financial reports in seconds.
Conversational & Search-Driven AI: Provide instant, contextually relevant intelligence with a scalable, cloud-based AI assistant.

Summary

Smarter Decisions. Optimized Portfolios. Higher Returns.

The AI Intelligence Engine for CRE empowers real estate professionals by automating intelligence extraction from diverse, unstructured data sources. Built on a secure, scalable cloud infrastructure, this AI-powered platform unifies siloed data, extracts insights from financial reports, lease agreements, and market research, and enables seamless decision-making through a conversational or search-driven interface. By eliminating inefficiencies, reducing risks, and unlocking new investment opportunities, this solution helps CRE firms enhance their portfolio performance and revenue potential.

The Main Problem

CRE Firms Struggle with Data Fragmentation & Inefficient Intelligence Extraction

Commercial real estate professionals deal with vast amounts of unstructured data like market reports, contracts, lease agreements, and financial documents. Extracting intelligence manually is slow, resource-intensive, and prone to errors, leading to delayed decision-making, missed investment opportunities, and operational inefficiencies. Without AI-driven intelligence, firms face high costs and scalability challenges in research, asset management, and portfolio optimization, making it difficult to execute data-driven, strategic decisions.

Real estate firms waste time manually extracting intelligence from unstructured data
Siloed data sources limit visibility and hinder decision-making
High operational costs from human-driven analysis and inefficient workflows

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Pain Point #1

Drowning in Unstructured Data?

Real estate firms rely on vast amounts of unstructured data—from market reports to lease agreements—yet manual processing is slow and inefficient. AI-driven automation extracts key intelligence instantly, ensuring professionals get the right insights at the right time to make smarter investment decisions.

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Pain Point #2

Struggling to Connect & Analyze Disparate Data Sources?

Data fragmentation across spreadsheets, internal reports, and third-party research slows down market analysis and deal sourcing. AI unifies these data sources and surfaces contextually relevant intelligence—providing real-time insights for portfolio optimization and better decision-making.

Pain Point #3

High Costs & Inefficiencies in Research and Analysis?

CRE professionals spend countless hours gathering intelligence, reviewing documents, and synthesizing data manually. AI-powered automation reduces reliance on expensive human analysts, allowing firms to scale research efforts, optimize transactions, and boost profitability without increasing operational costs.

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Don't just hear it from us

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JP Grace
Chief Technology Officer
Endear

As our customer base grew, we ran into PostgreSQL vertical scalability limits and problems like CPU, memory and connection exhaustion. We were thrilled the solution gave us a drop-in PostgreSQL replacement with much more efficient reads and writes. The solution requires less CPUs to hit our throughput and latency goals, lowering our cost by 40-50% and preparing us for the next phase of customer growth.

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See How It Worked For Other Businesses

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