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Startup of the day №23. A perfect real estate agent — Landly.AI, which finds the best options for estate investments

Wednesday, March 25, 2020

Investments in real estate are one of the most widespread ways to save and multiply the capital. The housing demand is guaranteed and investors have the possibility of receiving a passive income from the rent. The team of Landly.AI startup got interested in this direction and decided to make the investing process in real estate as convenient and profitable as possible.

Startup Jedi

We talk to startups and investors, you get the value.

Thanks to artificial intelligence, which lies in the basis of their work, the investor can choose specifically those objects that will bring him the most profit. What is more, you won’t need to deal with real estate agents. Dmytro Soloduha, the founder and CEO of the startup, told us about the project, their progress and goals.

About the startup

Landly.AI is a tool for those who invest in real estate. The service collects data about the real estates from various resources — from the floor-space, location, condition and up to price changes in a specific period of time. Basing on more than 80 parameters, the artificial intelligence that lies in the basis of the system operations, prognoses the value of a specific real estate object and signifies the factors which can help to increase the value of the object.

The service helps investors to save time and money expenditures for the market research. The startup works on the US market.



The idea

— How did the idea of creating the tool for investments in real estate appear?

— I was busy with other startups and was relocating a lot. I had to communicate with real estate agents and every time they drove me crazy. Like literally all of them. It seemed like these were the people who are parasites on a good market. I set up an Ambitious Goal to “eliminate” them:) But this was only the emotion.

In fact, I wanted to build a global service, something really useful. I studied metrics of successful startups, read articles with analytics and features of successful projects. It was all summarized by a fact that we needed a huge growing market. And the project has to be aimed at some minor changes that would: a) make the users’ lives easier; b) allow others to earn more and simpler; c) not change the market completely, just to satisfy the existing demand.

Further on, by studying various startups, I had a sneaky pic on a combination of solutions. I conveyed the analytics of what is proposed and understood how it can be improved, and continued with testing it on potential users.

— How much time did it take from the idea to its realization?

— The idea appeared somewhere in March 2019 and I started realizing it in April.

— Originally you are from Krasnodar but Landly.AI was launched in Israel. How difficult is it to launch a project there?

— It is quite easy. In Israel, there are all the means for this: accelerators, communities, investors, funds. It is much easier to launch a project here than it is in Russia. The only problem is the selection of specialists.

Click on the image to see Landly.AI's profile on Rocket DAO


The product

— Could you explain how the service works: the user registers, makes a request and what’s next?

— That’s quite a flexible moment, in fact, something I’m about to describe you now can be outdated tomorrow.

Now, the user registers, then he pays the subscription fee and we give him access. Then we are working on questions-wishes. The service is not automatized completely, we are still working on it.

Considering the subscription price, we still have only one subscription plan, conditionally a pre-sale — $5 per month. We’re planning to increase the price to $50 per month by this fall.


— Due to what functionality expenses would you increase the subscription value?

— Due to the free trial version, the asset tracker, a larger number of data resources, a higher result accuracy and a value booster.

Asset tracker is the asset manager. It is possible to add real estate objects and track the monthly guidance for 12 months ahead, and also see the history of updates — how the opinion of artificial intelligence changes. In addition, there will be recommendations like keep-sell-improve.

Sources of real estate data for sale. Plus, not only what is on sale but also what, theoretically, will be posted soon, as well as what is not on sale, but has good prerequisites for profitability. In other words, it’s possible to find such objects and try to negotiate with the current owner.

Plus, additional data resources from outer suppliers, analytic systems, statistics bureaus and others.

Increasing guidance accuracy is a huge sector of Research and Development. It includes data featuring, experiments and the algorithm combinations testing. In other words, it is a complete R&D.

— By value booster, you mean conditional advising set on what to do to increase the real estate’s value or something else?

— The system goes over the possible options for improving the selected house and estimates how it would change the market price. Then it chooses different combinations. Long story short, you can understand how to increase the house’s value with minor improvements.

— The service helps to find the best possible real estate for investing regarding 80 parameters. Could you please explain what the parameters are?

— Now, there are 80 but it is just the beginning. Those are the house characteristics: the number of rooms, bedrooms, floor-space, location, nearest schools, relation to the city and region, wall material, the roofing, the general floor-space. Plus additional indexes like the average price per square feet in this region, in this city, of such houses in the neighbourhood and so on.




The artificial intelligence

— What is the function of the AI: does it count the forecast cost or something else?

— In automatization. Notionally, we replace the “bunch of monkeys” which would do a specific task manually, lingeringly and at a high cost. We taught the machine to do this. It processes the information quickly, qualitatively and cheaply.

There is, for example, a set of indicators by which a person can approximately determine the market price of a real estate object, identify indicators of growth, and also, using the combination of these factors, say if this is a good object for investment or not.

Our AI does the same amount of work but:

  • analyzes 10 times more indicators;

  • processes the whole selection;

  • forecasts the return on investments (ROI);

  • ranges objects by ROI;

  • shortly explains what indicators have influenced the forecast.

In such a way, everything mentioned above can be done by 30–40 specialists in a few days while the instructed “iron lady” does it in a few seconds.

Of course, it is not only information processing but also its collection, updating, cleaning, verification and addition from several third-party resources. So, our client still does not waste time searching for real estate on a dozen sites. All in one place.

— How much time did it take to “teach” the service how to make estate prices’ prognosis?

— For 2 months we had been working on the first version that accumulated estate data from 10 cities in California and was managing around 80% of the market objects. The accuracy was also around 80%. It took 4 months to develop a more-or-less adequate version. Currently, the project is working in 329 US cities, and the accuracy of the guided real estate objects is 95%.

— Correct me if I am wrong: the client doesn’t waste time surfing other websites as your service gets the information from them?

— Yes, that’s correct. We are gathering data from the largest listings, later, we’ll add MLS (it’s a national database), social networks and estate agents’ sites. Long story short, we are collecting everything that can be collected, verifying and finalizing, adding something, and then selecting “the real thing”.



The goals

— What development stage are you at now?

— There are 3 parts of it:

  1. We have started the first sales, so we are now in the process of collecting the database, are working on conversion, etc.

  2. We are integrating new data sources.

  3. We are improving existing AI.

As the process goes, we are planning to add other useful functional features, are going to test various additional monetizing hypotheses. While we lack funding.

— How do you envision the project ideally in terms of functionality, markets, price?

— The vision changes almost once in two weeks. We are testing new hypotheses, trying different approaches.

The current vision is the following: we are aiming to create a system, where:

  • our agents and brokers will be able to earn more money;

  • developers will be able to sell their objects faster, with a smaller commission and without agents;

  • customers and investors will reduce agents’ payments.

Gett, Uber and Yandex Taxi in Russia have done something similar.




The market

— Why are you currently collecting data from the USA only?

— It is the world’s largest and most dynamic market. Europe, Asia, The Near East — almost everyone is investing in US estate.

In the US, there are 28 million accredited investors who are investing in the estate. According to the statistics, every third American (which is more than 100 million people) is investing or considering investing in the estate.

We don’t only find the objects to invest in or to buy but we also help to rate and track existing objects, as well as preparing the software that will show how to increase object’s value through simple renovations.

Our solution will be handy for both short-term investments: flip, renovation, renting-out and long-term investments.

— Do you consider working with other markets?

— Yeah, we do. We will be trying to create our next solutions for Great Britain, Germany, China. Maybe for Russia, but it’s not for sure. We are discussing a couple of pilot projects in Europe.

— What audience do you consider as a target one? How did you study it?

— Right now we are focusing on those who are investing in the estate and conduct up to 10 deals a year. However, we are planning to attract developers and agents as well, and maybe creditors.

We were looking for different audiences; contacted them, studied what services they use, what challenges they face and how they find a solution.

Our studies have shown that professional brokers and agents have access to the bigger amount of data and services when final investors have a considerably smaller amount of tools and data sources available. Besides, agents are trying to hide those tools from investors.

— How many clients does the service currently have?

— Not so many :) We are aiming to get the first hundred of customers within a month — these are individual sales. Right now we don’t possess enough money for a proper PR company, I contact clients and communicate with them by myself. As promotion channels, we are using cold emails, in-mails, LinkedIn messages, specially designated forums and groups.

After we get the first hundred, we will start testing different advertising channels.

— How do you understand who you should text?

— We have defined the target audience’s portrait but then everything is done manually — with the help of intuition. As mentioned above, now we are aiming at accredited and private estate investors that have around 10 deals per year and work with real estate.



— How much money did you need at the very beginning of your work? How and from which sources did you attract them?

— We didn’t attract any, managed to do everything without money.

— At all? I’m impressed!

— Not many people believed at first. But then started asking how we did it and if we could help them… And now they keep practising it. To be honest, it is a normal practice at a developed market: to get together and create a startup.

— What was the first step and how did you build the work after studying the startup experience?

— The project is done by People, Experts. I’ve spent a lot of time finding specialists and making deals with them. In the end, everyone worked and continued working for the sake of the idea and warrants.

So, I roughly determined what the stack would be about, what experts we needed and then was searching, choosing, communicating, “selling” the project, making deals, etc.

The most valuable thing is to find the right people. The team is the basis of every project. No matter what and how to do it, but who does it.

— Are you looking for investors now? How much money do you need for the startup to achieve the set goals?

— Yes, we are looking for investors and communicating with funds. We have a couple of scenarios on how to achieve the goals. One of them is to attract $200–250k to get $10k MPR (monthly recurring revenue — Startup Jedi) this summer.

— What is this scenario related to?

— It is one of the scenarios. The trick is in the following: we will develop the product to the state until we can be proud of it, automatize the majority of processes and check the main channels of attracting investments, and will understand how to scale the project. Then it will be the state when the project is ready to be scaled.

We will spend the money to form the sales department, to improve major solutions, and to automate the sales and development process.

Long story short, everything we need to:

  1. have a high conversion from a website user into a paying client;

  2. start generating many successful cases when we really helped our clients;

  3. increase the average cheque to $50 per month for the service package;

  4. achieve the revenue that amounts to $2000-$4000 per month, which will turn into $10 000 afterwards;

  5. be ready to attract the next financing round.

— Can you tell a few words about the second scenario for attracting investments and project development?

— Notionally, the second scenario means that we can start raising the seed round. In other words, to have a slow start now and expand it to 6–12 months.

— Is the investor’s geography important?

— The main feature of our solution is that it demolishes the barrier between the beginning and experienced investors. All this experience we packed in AI.

We present landly.AI as an AI-driven Realtor, as the market professional who specializes in the specified markets. In such a way, we destroy the barrier of experience absence and this also allows us to invest in areas, where investors haven’t worked before.

We act as an experienced real estate agent who will help to invest in new markets.

— Is the project profitable today?

— Yet, no. We have just started the sales, so we are growing.

— What are the monetization sources?

— We have a paid subscription. We plan to develop the product, increase the subscription price, add new tariffs and options to increase the average paycheck.



The team

— Which specialists were the most difficult to find?

— A designer and front-end developers. But it wasn’t difficult because there aren’t many of them. Designers are often irresponsible, frontends are usually spoiled by the attention to themselves and also aren’t very responsible once.

— What was the hardest thing while developing a startup? How and thanks to what you managed to overcome it?

— The hardest was to survive without money, confront the criticism and work in a state of constant pressure. Demented state of mind and bravery are the main mental resources of the entrepreneur:)

— How was your idea criticized and how the actual product answers the criticism?

— Different people are different in how they criticize, starting with the basic: “you can’t forecast the real estate price” and “such AI costs $2 million and 2 years of work”. There was also adequate criticism, such as “this is important for us, this is not; and we can find this on our own”, “there is such a thing as…, can you do it for us?”:)

In general, the criticism was aimed at the way we present our product, not at the product itself.

What is most important, based on objective criticism, we eventually implemented:

  • the transparency — we show the data that influenced the most the choice of the specific estate object;

  • the emphasis on the fact that we collect a lot of data to show to the client.




— Let’s imagine that the idea to launch Landly.AI hit you just today but in your mind, you already have the experience of launching startups and working with them. What steps would you avoid? And vice versa, what would you do at first?

— Unfortunately, it is unreal:) We spent way too much time on market research, Research & Development, understanding data sources, how to work with them and so on. It didn’t bring us any revenue but we received valuable experience and knowledge, which we monetize now.

If it was possible to receive all this knowledge volume instantly, we would have avoided the time loss.

At first, I would launch sales.

— What can you advise to beginning startups?

— Listen to nobody. Try to communicate with the target audience and clients as much as possible. Communicate, ask for pieces of advice but never take those words without a pinch of salt.

Try to start earning money from your product — the sooner, the better, even if there is no product and it is up to come. And never be afraid to change.


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