Machine Learning Development built for MarTech companies
What is Machine Learning Development?
We build ML systems engineered to stay accurate after deployment, not just in the notebook. For MarTech companies, this means navigating GDPR, CCPA while shipping fast.
Who needs Machine Learning Development for MarTech?
- Fragmented customer data across marketing tools
- Attribution modeling across multiple channels
- Real-time personalization at scale
- Models performing well in testing, poorly in production
- No retraining pipeline as data drifts over time
Best Machine Learning Development company
Marketing teams need data unification and automation more than they need another standalone dashboard.
Every MarTech company eventually needs reliable Machine Learning Development — we make that step less risky.
Talk to our MarTech Machine Learning Development specialists this week
Book a free 30-minute discovery callWhat's actually blocking MarTech businesses from shipping Machine Learning Development
- Fragmented customer data across marketing tools
- Attribution modeling across multiple channels
- Real-time personalization at scale
- Privacy compliance amid cookie deprecation
- Integration sprawl across the marketing stack
How we tailor Machine Learning Development to what MarTech teams actually need
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:
- GDPR
- CCPA
- CAN-SPAM Act
- ePrivacy Directive (EU)
Our Approach
We approach MarTech builds around the constraint that matters most: fragmented customer data across marketing tools. Every engagement in this space gets GDPR-aware data handling and compliance review before launch, not after.
See our case studiesTalk to our MarTech Machine Learning Development specialists this week
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 martech projects addressing challenges like fragmented customer data across marketing tools. We helped a martech platform improve campaign attribution accuracy by 34% with a custom data unification layer.
For martech clients, we pay close attention to GDPR, CCPA, 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 martech clients include fragmented customer data across marketing tools and attribution modeling across multiple channels. We tailor our discovery process to surface the specific version of these problems your business faces.