Custom AI,
Engineered To The Metal.
We design, train, and ship custom models, not thin wrappers around someone else's API. From data pipeline to deployed inference, we build the AI your product actually runs on.
A Wrapper Is Not A Moat.
Calling an API is a fine place to start. It is a poor place to stay. When AI becomes core to your product, owning the model changes the economics, the experience, and the edge.
Models Across Every Modality.
Whatever shape your data takes, text, images, audio, or signals, we build the model that understands it. Hover to explore each discipline.
Large Language Models
Fine-tuning, instruction-tuning, and RAG over your own corpus, with evaluation that keeps answers grounded and accurate.
Computer Vision
Detection, segmentation, OCR, and quality inspection models trained on your imagery and tuned for real-world conditions.
Predictive ML
Forecasting, classification, and scoring models that turn your historical data into decisions you can act on.
Speech & Audio
Transcription, diarization, and voice interfaces tuned to your domain, accents, and acoustic environment.
Recommenders & Ranking
Personalization and ranking systems that learn from behavior to surface the right item at the right moment.
Generative Models
Image, text, and structured generation built with guardrails, so creativity stays useful, on-brand, and safe.
Large Language Models
Fine-tuning, instruction-tuning, and RAG over your own corpus, with evaluation that keeps answers grounded and accurate.
Computer Vision
Detection, segmentation, OCR, and quality inspection models trained on your imagery and tuned for real-world conditions.
Predictive ML
Forecasting, classification, and scoring models that turn your historical data into decisions you can act on.
Speech & Audio
Transcription, diarization, and voice interfaces tuned to your domain, accents, and acoustic environment.
Recommenders & Ranking
Personalization and ranking systems that learn from behavior to surface the right item at the right moment.
Generative Models
Image, text, and structured generation built with guardrails, so creativity stays useful, on-brand, and safe.
How A Model Gets Made.
Data Engineering
We collect, clean, label, and version the data your model learns from, the part that decides everything.
Model Design
We choose the architecture and baseline, build vs fine-tune vs prompt, that fits your accuracy, cost, and latency targets.
Training & Tuning
We train, fine-tune, and optimize, tracking every run so improvements are measured, not guessed.
Evaluation
We test against held-out data and real edge cases with metrics tied to the business outcome, not just a leaderboard.
Deployment
We serve the model as a scalable, low-latency API or on-device build, wired into your stack and CI.
Monitor & Retrain
We watch accuracy, drift, and cost in production and retrain on a cadence, so the model stays sharp over time.
Data Engineering
We collect, clean, label, and version the data your model learns from, the part that decides everything.
Model Design
We choose the architecture and baseline, build vs fine-tune vs prompt, that fits your accuracy, cost, and latency targets.
Training & Tuning
We train, fine-tune, and optimize, tracking every run so improvements are measured, not guessed.
Evaluation
We test against held-out data and real edge cases with metrics tied to the business outcome, not just a leaderboard.
Deployment
We serve the model as a scalable, low-latency API or on-device build, wired into your stack and CI.
Monitor & Retrain
We watch accuracy, drift, and cost in production and retrain on a cadence, so the model stays sharp over time.
Built Like Real Software.
Notebooks do not survive contact with production. We build models with the same rigor as any critical system: versioned, tested, observable, and reproducible end to end.
PythonRustC++
PyTorch
TensorFlowJAX
Hugging Face
LangChainvLLM
pgvector
RedisSpark
MLflow
Ray
Docker
Kubernetes
AWS
Azure
Google CloudYou Own What We Build.
The trained model and its weights
Yours to own, run, and extend. No black box, no lock-in.
Documented architecture and data lineage
Every decision, dataset, and dependency recorded for your team.
Evaluation suite
Repeatable tests tied to the metrics your business actually cares about.
Inference API or on-device build
Deployed where you need it, wired into your stack and CI.
Monitoring and drift detection
Live visibility into accuracy, latency, and cost in production.
Retraining pipeline and runbook
So the model keeps improving long after we hand it over.
Frequently Asked Questions.
Not always. With transfer learning and fine-tuning we can get strong results from modest, well-curated datasets. Part of our job is finding the smallest data that does the job.
Describe The Model You Need
Tell us the problem and the constraints. We'll come back with an approach, a path to a working prototype, and an honest view of what it takes to run it in production.