Launching Q3 2026

Machine learning that actually ships

We help companies move from prototype to production. MaxML builds applied ML systems — reliable, scalable, and designed for the real world.

Be the first to know when we launch. No spam.

From research to revenue

MaxML was founded by a team of ML engineers and researchers who spent years watching great models die in notebooks. We decided to fix that.

Our focus is the gap between proof-of-concept and production — the part where most AI projects fail. We combine deep technical expertise with pragmatic engineering to deliver systems that work at scale, not just in demos.

Based in Europe, working globally. Currently in stealth mode, preparing for public launch.

2025
Founded
12+
Researchers
3
Patents pending

What we're building

Four core verticals designed to cover the full ML lifecycle — from data to deployment and beyond.

Natural Language Processing

Custom language models fine-tuned for domain-specific tasks — document understanding, entity extraction, semantic search, and conversational AI.

Computer Vision

Real-time image and video analysis pipelines. Quality inspection, object detection, medical imaging — optimized for edge and cloud deployment.

Predictive Analytics

Forecasting systems for demand planning, churn prediction, risk scoring, and anomaly detection. Built for accuracy and interpretability.

MLOps Platform

End-to-end infrastructure for model training, versioning, monitoring and serving. Automated retraining, drift detection, and rollback out of the box.

Pushing the boundary

Our team actively contributes to the ML research community. Select highlights from our pre-launch work.

NLP

Efficient fine-tuning of large language models for low-resource European languages

Exploring parameter-efficient transfer learning techniques that reduce compute requirements by 60% while maintaining benchmark accuracy. Preprint forthcoming.

Computer Vision

Lightweight defect detection architectures for industrial edge deployment

Sub-10ms inference on commodity hardware for real-time quality control. Collaboration with two manufacturing partners in the DACH region.

MLOps

Adaptive model monitoring with concept drift quantification

A novel framework for continuous evaluation of deployed models. Automatic detection and response to data distribution shifts without manual thresholds.

Interested in working with us?

We're selectively onboarding design partners ahead of launch. If your organization has challenging ML problems, we'd love to hear from you.

Get in Touch