Data Complexity and Volume
Traditional methods struggle to handle the scale and complexity of modern datasets
Custom AI pipelines, from raw data to inference at scale
Tailored AI pipelines designed and built by engineers who have run AI inference at scale.
Talk to a founder →Related things we’ve built.
- Echo Realms — a choose-your-own-adventure story project where we scaled AI inference to generate huge amounts of interactive content.
- NTC Slider Factory — lets anyone create text-to-image LoRAs from words alone, with no dataset.
Why Custom AI Pipelines Matter
Lack of Specialized Expertise
Building effective AI pipelines requires deep knowledge of both AI and data engineering
Integration Challenges
Connecting AI pipelines to existing systems and workflows can be technically demanding
A scope we can shape together.
These are starting points for a conversation. We’ll agree the scope and timing around your project.
For Data-Driven Startups
- Prototype AI Pipeline Development
- Data Processing Automation
- Predictive Analytics Setup
Typical Timeline: 4-6 weeks
For Growing Data Operations
- Real-time Data Processing Pipelines
- Machine Learning Model Integration
- Multi-source Data Unification
Typical Timeline: 6-10 weeks
For Enterprise-Scale Data Needs
- Large-scale ETL Pipelines
- Advanced AI Model Deployment Pipelines
- Cross-platform Data Orchestration
Typical Timeline: 10+ weeks
Technologies we use.
The problem decides the approach. These are some of the tools we reach for in this kind of work.
frameworks
- TensorFlow
- PyTorch
- DiffUsers
- ell
languages
- Python
- Scala
- SQL
tools
- ComfyUI
Talk to us about your AI pipeline
Email a few lines about what you’re building, what you’d like to improve, or where you’re stuck. Martyn or Mikkel will reply personally.
Or reach a founder directly: Martyn Garcia · Mikkel Garcia