Indianapolis-based MIBOR Broker Listing Cooperative (BLC) has announced a partnership with Gitcha to incorporate a buyer-focused listing service into its platform — expanding how agents access and share market data.

The collaboration introduces the Buyer Listing Service into the BLC, providing nearly 10,000 members with tools designed to surface real-time buyer demand alongside traditional property listings.

Leaders said the integration is intended to shift buyer activity from informal channels — such as private groups and personal networks — into a centralized system where agents can more easily collaborate.

MIBOR BLC President and CEO Shelley Specchio added that the move reflects an effort to evolve the MLS model by balancing visibility between buyers and sellers.

“MIBOR BLC must continue to evolve by deliberately strengthening the marketplace we are entrusted to facilitate,” she said. “When both sides of the marketplace are visible, cooperative, and respected, the entire industry moves forward together.”

Through the partnership, agents will gain access to structured data on buyer preferences, including desired locations property features budgets and financing timelines.

By centralizing that information, the organizations said the platform will allow members to identify emerging demand patterns and match buyers with available inventory more efficiently.

Gitcha founder and CEO Dan Cooper said the initiative builds on earlier collaboration between the two organizations.

“MIBOR BLC was an early visionary in recognizing how the MLS industry can support the agent community with better cooperation and insights by strengthening buyer representation,” he said. “They helped shape the platform, and they are leading the way for MLSs nationwide.”

Officials said the addition of buyer demand data could also benefit stakeholders beyond agents, including builders investors and local planners who rely on housing trends to inform decisions.

MIBOR BLC provides listing services across 17 counties in central Indiana.

This article was generated using HousingWire Automation and reviewed by a HousingWire editor before publication. The system helps convert company announcements and industry data into HousingWire-style news coverage.