Through 20 million addresses and 24 cities, how this startup sifts and digitises land and property data in India
Started by an economist and a lawyer, Terra Economics and Analytics Lab (TEAL) uses big data and machine learning to focus on solving the information asymmetry problem in land and housing in India.
Economist Kshitij Batra and lawyer Rohan Shridhar’s journey of founding Bengaluru-based Terra Economics and Analytics Lab (TEAL) demonstrates how problem solving can lead to unimaginable entrepreneurial solutions.
Kshitij was tracking property values in Indian cities while working on a project with the National Housing Bank and the Ministry of Finance when he realised there was a gap between what exists and what could exist.
Later, when he joined real-estate firm housing.com as a senior economist, Kshitij experimented with linking different property databases and running AI/ML algorithms to create tools for consumers. His next stint at IDFC’s think tank in Mumbai further exposed him to the supply of affordable housing in Indian cities. It also led him to Rohan, a lawyer specialising in the real-estate sector.
Passionate about their respective fields, Kshitij and Rohan started exploring the potential for creating a tech-enabled platform. After a few pilots with different databases across India, the duo decided to launch TEAL in 2018. Founded in Delhi-NCR region, the startup is now headquartered in Bengaluru.
What it solves
TEAL’s digital platform conducts property due diligence in real-time for banks, housing finance companies, individual buyers and sellers, lawyers, brokers, builders, and real estate investors.
“We collate land and property-related records from more than 900 different government agencies, courts, tribunals and other public data sources; and clean, prep and link this data using our proprietary AI/ML algorithms, and finally, make them searchable and accessible in real-time,” explains Rohan.
He adds that anyone who has dealt with real estate in India is aware of how opaque the sector is-- from all the complicated laws and regulations to unclear information about titles, disputes, unauthorised construction, and the actual transaction value of properties.
“Our flagship products, the TEAL Terminal and TEAL Check, enable enterprises and individual users to quickly extract relevant property information, review ownership documents and flag risks automatically. We currently have data for more than 20 million addresses across 24 cities, seven states and 20,000 localities, and are adding more every day,” says Rohan.
The TEAL Terminal is a subscription-based tool for banks, housing finance companies, law firms, brokerages and other enterprise clients to conduct property due diligence and risk assessment in real-time.
A more consumer-friendly version of TEAL’s application is called the TEAL Check, where anyone can go and request information about a property for just Rs. 40. The platform saw over 5000 registrations, and over 30,000 property queries in the last few months alone.
“TEAL Check is integrated with 99 Acres, and we are discussing additional features to incorporate with them to expand on the consumer-side,” adds Rohan.
During the pandemic-induced lockdowns, a lot of the government offices that dealt with property information remained shut. Many continue to operate at less than full capacity even after opening.
This is where the TEAL Terminal has been god sent for its users, as it enables them to gain property-related information digitally and in real time, without any dependency on government agencies.
“We are able to generate complete individual property level reports for our banking customers in the format that they require, which potentially minimises the time between logging in a loan application and disbursement,” says Rohan.
The startup also offers additional services like a dedicated WhatsApp channel for lawyers, brokers and real estate professionals to quickly request and receive property information.
“During the lockdown period, we saw an uptick in customer inquiries coming in from individuals looking to buy property. To service the volume of demand, we have created a consumer version where users can find property information easily,” Rohan explains.
Funding and challenges
For the first 18 months, Kshitij and Rohan bootstrapped TEAL, using savings borrowed from others to pay salaries and meet other expenses. Rohan also credits family and friends for other kinds of logistical support in running a business. The startup raised its first round of funding from Info Edge in November 2019 for Rs 5 crore.
What’s a good entrepreneurial journey without its fair share of challenges. For Rohan and his team, it was tackling the minefield of information.
He explains that land is a state subject so the rules, laws, regulations, governance mechanisms, as well as the systems of recording and documenting ownership and transactions vary across all 28 states in the country.
Nevertheless, the founding team’s strong background and knowledge about the sector held them in good stead.
In a country as diverse as India, another major challenge was sifting through the medley of information through different sources of records.
It often came in the form of multiple languages, inconsistent formats of record keeping, poorly scanned documents, unique dictionaries of terms, and no unique identifiers across different agencies to identify land and property units.
“We had to set up a strong data operation, and create our own systems to solve each of these problems, which had otherwise not been done by either the government or anyone else in the private sector,” says Rohan.
The team created their own translation engines, as most products wouldn’t work on text extracted from land records since their training corpuses had not seen the type of data and terminologies that are unique to recording land transactions. Read Khasra, Khatouni, Nakal, and Jamabandi!
The startup also created its own image recognition engine to read scanned documents with Indic languages, and cadastral maps of plot boundaries.
However, an ongoing challenge is getting enterprises and individuals to migrate away from legacy, manual, and offline processes and adopt digital solutions such as TEAL’s.
“While banks and housing finance institutions are increasingly taking to digitisation, mortgage lending remains the least digitised of all. There is a glaring absence of a digital mortgage lender in India, and even existing lenders rely on predominantly manual processes to process home loan and loan against property applications,” points out Rohan.
Market and future plans
According to the India Brand Equity Foundation (IBEF), the real estate sector in India is expected to reach $650 billion by 2025.
In the top seven cities, housing sales increased by 29 percent, and new launches saw a hike by 51 percent in the fourth quarter of FY21. Other players operating in the residential rental management space include NestAway, CoHo, Zenify, and others.
Currently, TEAL provides property information from over 24 cities in India.
“We are working on expanding our data coverage to additional Tier II and III cities since those have been identified as future growth markets for affordable housing by several of the financial institutions we work with. We are also expanding our analytics tools and capabilities such as geospatial features, property price estimation models and risk quantification to include more datasets, so that it can help our users,” concludes Rohan.
Edited by Anju Narayanan