Turning AI Strategy into a Scalable Intelligence Layer for Commercial Real Estate

HatchWorks AI first partnered with the firm through GenROI, our AI Strategy & Roadmap approach, to identify AI opportunities, assess readiness, and prioritize the initiatives with the strongest combination of business value and feasibility.

The next challenge was turning that strategy into production.

Rather than launching a collection of disconnected AI pilots, the firm wanted a reusable foundation that could improve access to enterprise knowledge, automate high-value real estate workflows, and support additional AI use cases as its broader transformation progressed.

HatchWorks AI designed and delivered a multi-agent Intelligence Layer on the firm’s existing Google Cloud environment. The initial release focused on three high-value capabilities: enterprise knowledge access, broker document generation, and title and lease abstraction.

By working within the firm’s existing systems and security model rather than duplicating enterprise data, the platform created a secure foundation that could expand as new AI opportunities emerged.

The firm had a broader AI transformation agenda, but moving from strategy into production required solving several practical challenges.

Enterprise knowledge and deal-related data were spread across multiple systems. Teams relied on manual, fragmented workflows to answer internal questions, produce broker-facing documents such as Broker Opinions of Value (BOV) and Offering Memoranda (OM), and extract structured information from title and lease documents.

The firm wanted to put AI to work across these workflows without creating another disconnected system or compromising the security and architecture already in place.

The solution had to meet four important requirements:

The engagement began with GenROI, HatchWorks AI’s approach to AI strategy and roadmap development. Through stakeholder discovery, readiness assessment, and opportunity prioritization, the team identified the initiatives best positioned to create business value and established a phased roadmap for execution.

With the priorities established, the engagement moved from strategy into build using Generative-Driven Development (GenDD), HatchWorks AI’s approach to building with AI. The team worked iteratively with the client, combining AI-enabled development with human ownership, verification, governance, and continuous user feedback as capabilities moved toward production.

The first three prioritized use cases became the foundation of the Intelligence Layer.

The engagement moved the firm from an AI strategy and prioritized roadmap into a production multi-agent Intelligence Platform supporting three initial business use cases and more than 70 users.

Teams now have secure, natural language access to enterprise knowledge while source data remains within the firm’s approved systems. Previously manual workflows around BOV and Offering Memorandum creation and title and lease abstraction now have dedicated AI-enabled workflows for document generation and structured extraction.

Just as importantly, the firm did not have to build separate architecture for each use case. The initial releases established reusable integrations, security controls, observability, and delivery patterns that can support additional agents and deeper integrations over time.

Instead of ending with a one-off AI pilot, the firm now has a production foundation for continuing to operationalize its broader AI strategy.