HelloData.ai was founded by a passionate team of data scientists and engineers with proven real estate domain expertise to help PropTech companies build data driven products. We’ve built real estate data data pipelines, predictive algorithms and workflow automation technology for startups, publicly traded companies, and everything in between.
NanoNets is a Deep Learning web platform that makes it easier than ever before to use Deep Learning in practical applications. It combines the convenience of a web-based platform with Deep Learning models to create image recognition and object classification applications for your business. You can easily build and integrate deep learning models using NanoNets’ API. You can also work with our pre-trained models which have been trained on huge datasets and return accurate results. NanoNets has leveraged recent advances in Deep Learning to build rich representations of data which are transferable across tasks. It’s as simple as uploading your input, generating the output and getting a functioning and highly accurate Deep Learning model for your AI needs. NanoNets is revolutionary because it allows you to train models without large datasets. With just 100 images you can train a model on our platform to detect features and classify images with a high degree of accuracy. NanoNets benefits you in four important ways: ● It reduces the amount of data needed to build a Deep Learning Model ● NanoNets handles the infrastructure for hosting and training the model, and for the run time ● It reduces the cost of running deep learning models by sharing infrastructure across models ● It is possible for anyone to build a deep learning model
No features have been listed yet.
HelloData.ai's answer
We use AI to analyze the quality and condition of apartment listing photos to assess comparability. This helps us deliver the best rent comp recommendations in multifamily real estate, with 9/10 overlap with appraiser selected comps.
We collect listing data from millions of apartments every day at the unit level, so we capture the last listed rent before each unit is removed from the market. This rent is within $5-10 of actual leases on a rent roll based on several tests with clients.
We benchmark operating expenses using a model trained on over 25,000 multifamily properties, which delivers highly accurate expense benchmarks in any U.S. market.
HelloData.ai's answer
In under 1-minute, you can complete a full market analysis with rent comps, expense benchmarks and real-time data with HelloData.ai. Our platform is very reasonably priced for the functionality (no one else offers the same capabilities), and we offer a 7-day free trial.
HelloData.ai's answer
Real estate investors and property managers are our main clients. We typically work with acquisitions and asset management teams from large real estate owners, but we also have many appraisers, brokers and lenders using the platform.
HelloData.ai's answer
This is our 2nd startup. We sold the first one, Enodo, to Walker & Dunlop in 2019. After building incredible internal products for W&D for 4 years we are back at it again with HelloData.ai, leveraging recent advancements in AI to deliver the most sophisticated real estate market analysis product in multifamily.
HelloData.ai's answer
Python, PostgreSQL, and Vue.JS
HelloData.ai's answer
Greystone, Redwood Living, and Luxury Living
I've worked with the HelloData.ai team on data extraction and revenue management projects, and they are seriously skilled in real estate data science and engineering. It's rare to find a team that understands real estate as well as they understand technology. These guys are super responsive and always understand what I'm talking about when it comes to real estate. I can't recommend them highly enough!
Based on our record, Nanonets seems to be more popular. It has been mentiond 6 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Want to automate repetitive manual tasks? Check our Nanonets workflow-based document processing software. Source: about 2 years ago
Nanonets is a no-code, workflow-based, and AI-enhanced intelligent document processing platform. It automates all document processes and is built on a robust, intelligent, self-learning OCR API that allows users to extract required data from documents in minutes. Source: about 2 years ago
Check out our website here https://nanonets.com/ for more. We also have some free tools where you can experience our product for free (like https://nanonets.com/online-ocr). Source: about 2 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: over 2 years ago
We will be using Python3.6+, Django web framework, Nanonets for character extraction from an image, Cloudinary for image storage and Google Search API for performing the searches. - Source: dev.to / over 2 years ago
Able2Extract Professional - Able2Extract PRO is a PDF solution for business and home users with high-fidelity OCR that allows users to convert PDF to all major formats, edit PDF text, forms, and pages, annotate, redact and sign any PDF and much more on Windows, Mac and Linux.
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
Bluebeam Revu - The end-to-end digital workflow and collaboration solution trusted by over 1 million AEC professionals worldwide. Revu delivers award-winning PDF creation, editing, markup and collaboration technology designed for AEC workflows.
DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.
ListingAI - GPT-4 AI generated marketing materials (listing descriptions, social media content, landing pages and more) for real estate.
Amazon Textract - Easily extract text and data from virtually any document using Amazon Textract. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.