#USA #New York #commercial real estate #Friedman Real Estate #Leni AI

Friedman Real Estate and Leni's Collaboration on Reporting Workflows

In an exciting development for the commercial real estate sector, Friedman Real Estate has partnered with Leni to revolutionize their reporting processes. By utilizing Leni's advanced AI infrastructure, Friedman is creating automated reporting agents and workflows tailored specifically to their operational needs. This innovative approach allows Friedman to build custom solutions rather than relying on off-the-shelf reporting products that often fall short of unique business requirements.

The Need for Customization

As Friedman expanded its portfolio and embraced additional properties, the demand for tailored reporting solutions escalated. Each property and investor often requires slightly different metrics and reporting formats, resulting in a slew of diverse requests that needed to be addressed with precision. Traditional methods often meant manual gathering and assembly of data, which was time-consuming and prone to errors. Recognizing the need for agility and adaptability, Friedman sought a solution that would enable it to streamline these processes.

Leni's AI Infrastructure Advantage

Leni's infrastructure provided exactly that. Instead of developing a unique engineering solution from scratch, Friedman leveraged Leni's platform to connect their existing data sources, which includes various ERP and accounting systems. This integration is powered by Leni's proprietary Universal Data Model, compatible with nearly 85% of such systems, allowing Friedman to extract and manipulate data without the need for extensive setup or modifications to their existing frameworks.

Building Workflows with Context

Friedman's first workflows focus on custom reporting, drawing data from their existing systems and incorporating Friedman's own definitions and review processes. By using Leni's technology, they have managed to automate the production of reports and dashboards in their preferred formats. The processes that previously required multiple personnel and separate systems can now run as a seamless workflow that is easily adjustable to accommodate new requests or changes in data definitions.

The ability to create these reports without waiting for vendor input gives Friedman greater control over its operations. Every output retains traceability back to its source, ensuring that all stakeholders can verify the integrity and accuracy of the reports generated.

Efficiency and Cost-Effectiveness

According to Leni's published research, adopting this infrastructure not only boosts accuracy by 7-15 percentage points but also significantly reduces the costs associated with reporting. In practice, the system has delivered over 99.6% task accuracy while cutting the overall costs by about two-thirds compared to other frontier models. Each output is documented, allowing for comprehensive audits and checks that enhance reliability.

A Shift Towards Independence

The partnership between Friedman and Leni signifies a shift in how real estate firms can approach reporting and data management. Historically, companies have depended on external providers for such solutions, often leading to stagnation when adaptation or changes are needed. Friedman’s ability to construct its own reporting agents means they can quickly respond to market demands, tailor reports to unique scenarios, and capitalize on emerging opportunities without the draw of lengthy development cycles.

Insights from Leadership

Jared Friedman, Co-CEO of Friedman Real Estate, emphasized, “We did not want another reporting product that we would immediately need to change. We wanted to build our own workflows, and Leni's infrastructure is what made that possible.”

Arunabh Dastidar, Co-founder and CEO of Leni, remarked, “Friedman built reporting agents first because reporting hurt the most. The point is that the context layer belongs to Friedman, and every workflow it builds next runs faster and cheaper on it.” This reflects the growing trend of companies seeking to gain autonomy over their operational processes through technology.

Conclusion

As the commercial real estate landscape continues to evolve, initiatives like the one between Friedman and Leni will pave the way for more firms to leverage AI and automation. By enabling businesses to define and execute their own workflows, the future of real estate reporting looks not only more efficient but assuredly more tailored to individual company needs. Friedman’s ingenuity in capitalizing on Leni's capabilities will likely serve as a blueprint for others looking to innovate in a traditionally rigid sector.