No-code Data Analysis

Savills empowers their brokers with Augmented AI's "action services' integration to Enterprise Open AI.

Customer:

Savills

Industry:

Commercial Real Estate

Country:

UK/United States

Business Background:

A multinational commercial real estate firm, operates with a forward-thinking US arm that embraces innovation and drives progress independently. With a focus on enhancing efficiency and market development, the US team has integrated ChatGPT enterprise AI licenses within their broker teams. A prime example of this integration is the connection of ChatGPT to a comprehensive large dataset of commercial leases in the US, which is essential for brokers searching for potential clients across various industries and locations.

Downloads:

Savills Summary PDF Final

March 23, 2024

Problem

The obstacle was clear: the scalability of accessing the core lease data was hindered by the limited availability of research teams in contrast to the large number of brokers. This discrepancy created a bottleneck, as the brokers were dependent on the researchers to extract vital information from the database. The challenge was to devise a secure and user-friendly GPT interface that would allow brokers to self-serve this information efficiently, which would be a revolutionary step for the company.

"Action services are more than just an innovation; they represent a paradigm shift in how non-technical personnel interact with complex data systems, making previously inaccessible information readily available at their fingertips."

- Larry Arnstein, Chief Technical Officer, Augmented AI

Solution

Augmented AI addressed this challenge for its customer by creating 'action services,' a symbiosis of front-end web application and back-end API that GPT actions can access effortlessly. This system authenticates users and allows brokers to articulate their data needs in simple English. The GPT aids them in refining their searches and delivers precise results, including links to download the relevant datasets. This solution not only bridged the gap between brokers and the data but also implemented necessary controls for data safety and policy compliance.

Outcome

The initiative resulted in a dual triumph: firstly, it extended the capabilities of GPT beyond its prior limitations, and secondly, it established a framework for secure authentication. This breakthrough enabled brokers to independently query a vast data set, empowering them to operate without the constant need for research team support. Additionally, the creation of this 'action service' structure has paved the way for its application to various other enterprise resources within the company, heralding a new era of efficiency and self-sufficiency.

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