iOi Hackathon Data Provider: Enodo

enodo logo

With about a week to go before our iOi Summit in San Francisco, we wanted to let everyone know about another one of our data providers, Enodo. Enodo uses artificial intelligence and machine learning to analyze multifamily property information from across the country and present key investment takeaways in an easy-to-understand dashboard, cutting out the confusing tables and forms usually associated with underwriting these properties.

Enodo takes data from leading property data sources and brings it together in a digestible way to allow for property managers, investors, and other CRE professionals to make key decisions about their multifamily properties. Enodo’s software looks at about 2 million properties weekly, analyzing all that data together and using it to help users understand comparable property rents, amenities, and more.

For the iOi Hackathon, Enodo is providing our contestants with multiple tools that look at dozens of different metrics surrounding multifamily properties. These tools include Enodo’s:

– Amenity Parsing Utility
– Rent Prediction Tool
– Operating Expense Prediction Tool
– Comparable Property Detection Tool
– Amening Pricing Query Tool

These predictive analytic tools can be used with other API providers in our hackathon to create comprehensive real estate technology solutions, and we are looking forward to seeing how our participants use Enodo in their projects!

iOi Hackathon Framework Sponsor: Lyrebird

A picture of the lyrebird logo, with their tagline 'we create the most realistic artificial voices in the world'

We are almost a month away from our iOi Summit in San Francisco and the in-person part of the Hackathon. The sponsor I wanted to highlight today is called Lyrebird and they offer a truly innovative service. Lyrebird’s AI is built for synthesizing real people’s voices and producing some uncanny replication of voice.

I’ve demonstrated this to people in the lab and they are very surprised about how much it can actually sound like my voice. I tried out their system by reading in 70+ sentences supplied by Lyrebird, so they can map my voice to the text and understand how I pronounce vowels, consonants and my cadence.

I’ve included three recordings of my voice below:

Now, Lyrebird’s system maps my voice and produces a voice that can then be used for my purposes. For each of the recordings below, I typed in text and the software read it in my digital voice. You will hear some buzzing in this and that is because when I recorded this, I was in a room with fans running. But, I have to say, this is pretty cool to hear my voice in its synthesized form:

Where I see this working in real estate is for the final recording talking about property amenities. Imagine data from your listings is fed into your synthesized voice and it could read them out for a client.That could be used to communicate with clients when you are not available. Pretty cool.

I want to highlight a pretty special use case of this technology outside of real estate. Lyrebird has partnered with the ALS association to create Project Revoice. Remember the Ice Bucket Challenge? Well it turns out that the founder of the challenge, Pat Quinn, has lost his voice because of ALS. Lyrebird has helped create a synthesized voice for his computer that is more his own. Check it out below:

Thank you to Lyrebird for sponsoring our Hackathon and providing their Framework API!!

iOi Hackathon Framework Sponsor: restb.ai

This is a picture of a kitchen demonstrating the capabilities of software by restb.ai. It shows the software identifying features in the kitchen. It identifies stainless steel appliances, a kitchen island, tile floors and natural light.

restb.ai’s software identifies features in a home and generates natural languages for use in all sorts of applications.

We’ve been putting a lot of time into the Hackathon (click here to register) for the iOi Summit, finding good data sources, benefits to the participants, and frameworks they can use. The first sponsor for the Hackathon I wanted to highlight is called restb.ai, which is an example of a company using artificial intelligence and machine learning to create natural language that describes what’s in a picture. Their technology will analyze images you provide and create data sets in the following areas:

  1. Room Type Classifcation
    • Identifies over 30 different room scenes like ‘living room’, ‘kitchen’, ‘bathroom’, etc.
  2. Home Feature Tagging
    • Identifies more than 30 features in the home based on room type. Things like ‘vaulted ceilings’, ‘hardwood floors’, and ‘natural light’.
  3. Exterior Style Classification
    • Has learned 16 different architectural styles for classification purposes.
  4. Logo & Watermark Detection
    • Can identify if an image already has a watermark or logo placement on it.

What’s cool about this type of software is that it creates text data for you on the fly and allows you to do things like populate the machine readable fields for images. It could be used to create listing details, or to create keywords for searches on listings and provide better results.

 

restb.ai will provide access to their API for all hackathon participants to use. We want to thank them for participating! Have you registered for the Hackathon? To find out more and register, click here.