Services
AI, Machine Learning & Computer Vision
We build AI that actually earns its keep: custom models trained on your data, language features like assistants and document tools, and computer vision that runs in real time. And we take it all the way to production, then keep it healthy once it's live.
What we build
AI that does real work for your business.
- Custom machine learning models trained on your data
- LLM-powered product features and assistants
- Computer vision for detection, tracking, OCR, and spatial mapping
- Automation for the workflows that currently eat up human hours
From prototype to production
We start with a data audit and a feasibility check, build models with honest evaluation metrics, then deploy to cloud or edge/mobile with monitoring and retraining loops. We'll also be straight with you when a simple rules engine beats machine learning, and save you the spend.
Where AI meets 3D
Because we build XR too, we're unusually strong where vision meets 3D: hand and body tracking, scene understanding, and AI-driven behavior inside immersive products. It's one team across both disciplines.
Tech stack
- Python
- PyTorch
- TensorFlow
- OpenCV
- LLM integration
- Edge & mobile inference
What you get
- Trained models and weights
- Inference APIs
- Evaluation reports
- Deployment infrastructure
- Integration code
Related work
Browse our portfolioCommon questions about AI/ML & Computer Vision
Not always. Plenty of problems get solved by fine-tuning an existing model, using pretrained vision or language backbones, or augmenting a modest dataset. Our first step is a data audit that tells you honestly what's feasible with what you have, and what's worth collecting.
Usually fine-tune. Training from scratch is expensive and rarely worth it outside specialized domains. We start with the most capable pretrained foundation that fits, then fine-tune or build a retrieval layer around it. And we back the choice with cost and accuracy numbers so you can see the reasoning.
It comes down to latency, privacy, and cost. On-device (edge/mobile) is the better fit for real-time, offline, or privacy-sensitive use. Cloud is better for large models and centralized updates. We'll optimize the models for whichever you choose, and run a hybrid setup where that makes sense.
You do, on the same terms as the rest of your deliverables. Once you've paid in full, the models, weights, and integration code we build for you are assigned to you. The only thing we keep is our pre-existing internal tooling that predates your project, and you're licensed to use that within your product. The specifics live in the service agreement we sign together.
Let's build it
Tell us what you're trying to make. We'll come back with a clear scope, a timeline, and an honest estimate.