Hosta Labs
To promote physical and mental health: our technology scans indoor and outdoor environments with the simplicity of taking pictures. We identify objects, colors, object placement, measurements (proportions), and object quantities, architectural structures, and sustainability of a building, amongst other things.
As such, we can setup a database of different spaces and create benchmarks/ best practices for urban planning. New captured data can be used to find relationships between objects/correlations between existing and benchmark conditions to promote a health/green/sustainable/etc. score. The score determines whether a physical place meets the criteria for a healthy living environment based on predefined acceptable conditions.
Currently it takes intense investments into technology to determine a correlation of health and the environment. Our technology needs as much as a picture with a regular camera to extract metadata of the environment and establish health scores to improve the health of a city.
Our target group can be governments, real estate organizations, or other entities involved in city planning. We can help to increase efficiency in converting current space into healthier living spaces but we can also help from an analytical perspective by providing scores of current "healthiness" of the environment.
The solution is an Machine Learning algorithm that converts simple pictures of indoor and outdoor living spaces into data of:
- Dimensiones
- Object location
- Spatial data
- Color schemes
- Material used
This data can be stored in a database to capture insights of different spaces and create benchmarks/ best practices for urban planning. New captured data can be used to find relationships between objects/correlations between existing and benchmark conditions to promote a health/green/sustainable/etc. score. The score determines whether a physical place meets the criteria for a healthy living environment based on predefined acceptable conditions. Ultimately, it can be used to create 3D models to improve current spaces.
- Enable equitable access to affordable and effective health services
- Prototype
- New technology
Patent pending solution on Machine Learning. Algorithm solves unsolved problems in Machine Learning:
1. the visual recognition of dimensions(i.e. creating an automated 3D model with estimated measurements of a room)
2. the relationship of objects towards another (i.e. a window belongs to a wall)
3. the identification of an object in a building (i.e. openings in a wall)
And all it takes is a picture with a standard smartphone camera.
All this data can be stored in a database in order to derive insights of the healthiness of the environment. Correlation with other indicators can be drawn and hence, urban planning guidelines can be derived that account for a healthier environment.
Due to the degree of automatization, the solution is cheap and scalable.
We are able to transform images into data, a 3D model, or floor-plans and other important information about the built environment. We use a machine learning algorithm that detects built environment information such as walls, openings, doors as well as the objects that are contained within from images captured with a smartphone. No special equipment required.
- Artificial Intelligence
- Machine Learning
- Big Data
First and most straight forward, the solution creates efficiency in the renovation process of buildings, leaving more resources for the actual renovation by reducing the time of recreating a digital model and a floor-plan from several hours to seconds. This is especially important for the low-income targeted real-estate. Further, the data that can be captured can be used to create "healthiness" indices which in turn can be the basis for urban development decisions.
Ultimately, we aim for indirectly addressing every citizen by introducing the solution in the areas of government, home improvement, and home insurance.
- Elderly
- Rural Residents
- Peri-Urban Residents
- Low-Income
- Middle-Income
- Persons with Disabilities
- United States
- United States
B2B solution (serves for institutions who serve people) - numbers refer to businesses served.
Current number of companies: 3 (serving >1,000 people)
Number of companies in 1 year: 45 (serving >10,000 people)
Number of companies in 5 years: 10,000 (serving >100m people)
Within the next year: find product-market fit - building your brand in the right market (real estate health and home improvement)
Within the next five years: scale massively, fully automate, develop ad-on solutions.
1. Sufficient funding
2. Enter reasonable sized customers in time (purchasing cycle of larger corporates)
3. Finding the right partners/suppliers/vendors and building the resources to scale the business and enter the market
1. Fundraising
2. 2-way Sales Strategy: Small-Medium business as a fundament, focus on large institutions to pilot the software
3. Collaborate with Indian Service Providers to overcome the phase of automatization
- For-profit
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4 full-time
2 part-time
no contractors
Rachelle: former MIT PhD student in computer visioning and planning and architecture - the technical brain
Daniel: planning and architecture undergrad and law grad - legal and financial brain
Henriette: MIT Sloan Fellow with 11 years in strategy, consulting and management - Business Dev and Strategy
Carlos 1: 7 years of Marketing & Social Media experience - Marketing expert
Carlos 2: MIT PhD student in computer engineering - Fullstack Developer
Laura: MIT PhD student in computer engineering - Fullstack Developer
Design X - leveraging investor landscape and advisory
Products:
- API as SaaS solution
- 3D Models & Floorplans
- Environmental Data
Customers:
- Governments
- Real Estate
- Planners/ Architects
Impact:
- Efficiency --> cost advantage "cheaper than the draftsman"
- Measurements for a healthy environment
- Enabling experimental planning
Create revenue with the products:
- patent pending
- API as SaaS solution
- 3D Models & Floorplans
- Environmental Data
- Optional at later stage: licensing
Solve can help us overcome the entry barrier to larger institutions by establishing trust and providing publicity.
- Distribution
- Funding and revenue model
- Media and speaking opportunities
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Customers: Real estate, home improvement, urban planning governmental organizations (Recommendations & Referrals); WeWork - Real Estate Health
Marketing: Society of Architecture & Designs, Sustainability & Construction, Tech in Construction
Definitely want to apply as we solve to date unsolved problems in AI technology.
We would use the price to market our product as it needs explaining and to reach a tipping point marketing and publicity is required.
Advancement in the solution will be made as follows:
- full automatization of the product
- optimizing the already small error rate
- providing a user-friendly front-end
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Definitely want to apply as we solve to date unsolved problems in AI technology.
We would use the price to market our product as it needs explaining and to reach a tipping point marketing and publicity is required.
Advancement in the solution will be made as follows:
- full automatization of the product
- optimizing the already small error rate
- providing a user-friendly front-end
Definitely want to apply as we solve to date unsolved problems in AI technology.
We would use the price to market our product as it needs explaining and to reach a tipping point marketing and publicity is required.
Advancement in the solution will be made as follows:
- full automatization of the product
- optimizing the already small error rate
- providing a user-friendly front-end
Co-Founder
Co-Founder