Investment decision-making requires adequate information and data. This enables investors to make quick decisions, having understood all areas of the investment. The world of real estate is no exception. Data accessibility is important for real estate investors, managers and owners as it helps them make informed investment decisions within the appropriate time frame. Accessibility of information also allows real estate investors to properly analyze trends and make well-thought-through investment decisions in time to meet up with deadlines and timelines. For instance, data regarding home equity, mortgage payments, age of property, and data about the current tenants and their leases, help investors in determining the right property, value and potential, while helping to create a sense of fairness among parties.
According to report, the Global Business Intelligence Market was at USD 24.59 Billion in 2022, with a growth estimation of USD 41.94 Billion by 2030. This represents a Compound Annual Growth Rate (CAGR) of 6.90% over the forecasted period. Furthermore, the Artificial Intelligence (AI) sector within the Real Estate Market, which encompasses IoT, was valued at USD 163.46 Billion in 2022. This figure is expected to surge to USD 1335.89 Billion by 2029, growing at a remarkable CAGR of 35%. This also takes into account that North America represents about 50% of the global market in both the Business Intelligence and Artificial Intelligence domains. These present opportunities of potential growth for the real estate industry.
Despite how critical the availability and accessibility of data are to real estate investment, industry practitioners still make decisions with a chain of scattered excel spreadsheets managed by hundreds of analysts. This creates a bottleneck across the industry, slowing down activities and resulting in the loss of millions of dollars in daily transactions. According to research, Over 47 million rental assets across North America comprise one of the biggest asset classes for many institutional and private equity investors worldwide.
Despite holding over 43 trillion dollars of assets, this asset class is still reported and managed using pieces of unorganized data, gathered across multiple channels and layers of operations, by analysts, to attempt to meet quarterly reporting requirements for brokers, asset managers, and owners. This manual method gives room for mistrust and unaccountability. This inefficient reporting and decision-making structure also renders asset owners and managers vulnerable to cost overruns, budget overruns, and lost deals, hampering long-term returns. These inefficiencies across asset life cycles cost more than $5.5 billion yearly to enterprise rental managers and investors in North America.
Realsage is a company that focuses on redefining the way the real estate industry makes decisions, leveraging artificial intelligence to obtain data. Having an understanding of the potential of AI and all the possibilities it holds, Realsage is already working ahead to leverage AI for improved real estate experience.
Co-founder of Realsage, Arnab Dastidar says the Realsage team combines their deep experience in real estate with their banking and technology expertise and applies it in offering cutting-edge solutions at Realsage. According to him, due to the fragmented state of data, larger enterprises spend approximately 28% of management time attempting to gather information from various teams and portfolios in order to make critical decisions. He adds that this inefficient use of time leads to significant losses.
Dastidar laments how rental managers face daily challenges around decision-making, noting that Realsage aims to change that for the entire industry. According to him, the company makes it simple, fast, and accurate to review, assess, and seamlessly take data-driven decisions. He reveals that Realsage’s AI platform quickly organizes and leverages data across a variety of internal and external data sources to generate fast, real-time actionable insights for enterprise asset owners and managers.
“For instance, consider a use case where an asset manager wants to ensure that their assets are performing competitively and determine where to invest their next dollars for improvements. Instead of manually entering data into Excel models, the manager can easily incorporate multiple data plugs, including external data such as rental data, trends, and demographics, as well as internal data such as asset rent rolls and unit turnover, to analyze and visualize the data. This will allow them to decide which CAPEX project will generate the highest ROI,” Dastidar notes.
On his part, another co-founder, Gaurav Madani, who also doubles as the company’s Chief Revenue Officer, says the system has the ability to memorize specific information and re-apply it to provide new insights.
“Over time, the system will recognize changes in these sets and use unique deterministic AI models to provide predictive and prescriptive insights. These point out investment opportunities, benchmark changes, revenue improvements, or cost savings based on the manager's preferences. Essentially simplifying and accelerating the entire decision-making process, making it 10x more efficient for the organization.
It results in capital allocators closing more deals, asset managers managing bigger portfolios, and enabling property managers to generate more returns,” Madani explains.
Speaking about the company’s competitive landscape, Zain Nathoo, who is a third co-founder, adds that Realsage’s goal is to empower multifamily teams across the world with the best tools to make data-driven decisions.
“Our competitive landscape consists of various software options, including niche offerings that overlap with our product and modern multifamily property management suites that feature some business intelligence elements. We see RealSage becoming the go-to platform, leveraging cutting-edge AI and data-driven insights to transform traditional decision-making processes into agile, informed, and impactful choices,” Nathoo concludes.
Media Contact:
Name: Arunabh Dastidar
Email: [email protected]
