Machine Learning Development built for PropTech companies
What is Machine Learning Development?
We build ML systems engineered to stay accurate after deployment, not just in the notebook. For PropTech companies, this means navigating Fair Housing Act (US), Local landlord-tenant laws while shipping fast.
Who needs Machine Learning Development for PropTech?
- Manual property management workflows
- Tenant communication and maintenance request friction
- Disconnected leasing and accounting systems
- Models performing well in testing, poorly in production
- No retraining pipeline as data drifts over time
Best Machine Learning Development company
Property management software needs to satisfy landlords, tenants and compliance teams simultaneously.
We work with PropTech leaders in to plan and deliver Machine Learning Development without the usual delivery surprises.
See how GarudLabs can deliver Machine Learning Development for your team
Book a free 30-minute discovery callWhat PropTech leaders in wish they knew before starting Machine Learning Development
- Manual property management workflows
- Tenant communication and maintenance request friction
- Disconnected leasing and accounting systems
- Smart building IoT integration complexity
- Compliance with local rental regulations
From discovery to deployment: our Machine Learning Development process for PropTech
ML model architecture and training pipeline
Feature engineering and data pipeline
Model deployment and serving infrastructure
Drift detection and retraining automation
Experiment tracking and model versioning
Core Technology Stack
PythonPyTorchscikit-learnMLflowKubeflowAWS SageMaker
Timeline, investment & compliance
Typical timeline
8-16 weeks
Typical investment
$25,000 - $170,000
Machine Learning Development engagements in this combination typically need to account for:
- Fair Housing Act (US)
- Local landlord-tenant laws
- GDPR (EU)
- Building safety codes
Proven Results
"We helped a property management platform reduce maintenance request resolution time by 45%."
Read the full case studyStop guessing on Machine Learning Development — let's build a real plan together
Get a free project cost estimateFrequently Asked Questions
Most Machine Learning Development engagements take 8-16 weeks, depending on scope and how clear the requirements are upfront. We'll give you a firm timeline estimate after a short discovery call, not a generic range.
Machine Learning Development projects with us typically range from $25,000 - $170,000, scaled to the complexity of your requirements. We provide a detailed, itemized estimate before any work begins so there are no surprises mid-project.
For machine learning development, we typically work with Python, PyTorch, scikit-learn, MLflow, chosen based on your specific scalability and integration requirements. We're not tied to a single stack and will recommend the right tools for your situation rather than our default.
A typical machine learning development engagement includes ml model architecture and training pipeline, along with the other deliverables outlined in our proposal, such as documentation and a post-launch support window. The exact scope is tailored to your project during discovery.
Most clients come to us for machine learning development because of models performing well in testing, poorly in production, among other related challenges. We start every engagement by mapping your specific pain points before writing a single line of code.
We've delivered multiple proptech projects addressing challenges like manual property management workflows. We helped a property management platform reduce maintenance request resolution time by 45%.
For proptech clients, we pay close attention to Fair Housing Act (US), Local landlord-tenant laws, building these requirements into the architecture from day one rather than retrofitting them later. We'll confirm which specific regulations apply to your business during discovery.
The most common challenges we solve for proptech clients include manual property management workflows and tenant communication and maintenance request friction. We tailor our discovery process to surface the specific version of these problems your business faces.