Commercial Real Estate Agency
A leading London commercial real estate agency engaged dadoAI to build an AI-powered deal sourcing engine that continuously monitors thousands of data sources, identifies off-market acquisition opportunities, and predicts which property owners are ready to sell before competitors find out.
Sector
Commercial Real Estate
Timeline
8 weeks
Location
Dublin
Service
AI Deal Sourcing & Market Intelligence
The Problem
Agents spent every morning manually searching planning portals, Companies House filings, local authority notices, and property news trying to spot signals that owners might be considering a sale. The research was duplicated across the team with no systematic approach, no shared intelligence, and no way to monitor thousands of potential opportunities simultaneously. The problem wasn't lack of market knowledge but lack of scalable intelligence gathering that could identify opportunities before they became public. Manual research meant each agent could only track 20 to 30 potential targets effectively. Off-market deals were missed simply because no one could process enough data points simultaneously to spot the signals. Opportunity identification was reactive rather than predictive. High-value acquisition targets were found through luck and personal relationships rather than systematic data-driven intelligence. Time spent on research was time taken away from client relationships and deal-making.
Solution
Implementation involved sophisticated AI monitoring across multiple data streams running continuously. Planning application scanning identified development opportunities and zoning changes that created acquisition value before competitors noticed. Companies House analysis flagged businesses in financial difficulty, restructuring, or administration that might need to divest property assets quickly. Ownership change tracking identified corporate restructures and estate situations that created motivated seller scenarios. Market intelligence correlated thousands of signals simultaneously to generate predictive seller likelihood scores, combining lease expiry data, tenant financial performance, comparable transaction patterns, and macroeconomic indicators. Opportunity ranking prioritised targets by probability of sale and potential deal value, allowing agents to focus effort on the highest-impact targets. Real-time alerts notified agents immediately when high-priority opportunities emerged, ensuring first contact before any competitor. The system learned continuously from successful acquisitions, improving its pattern recognition and opportunity scoring over time.
Testimonial
Director
Commercial Real Estate Agency
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