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Own your models.
Own your data.
Save your coins 💰
We use QAT and other techniques to make deploying internal LLMs 120x cheaper than proprietary APIs. Get the 2026 ML Training Cookbook to learn how to train and deploy your own models.
We build, deploy, and maintain your domain AI.
From raw documents to a deployed model running on your infrastructure — we handle the pipeline end to end. You own the weights. Your data never leaves your environment.
Data Pipeline Engineering
We connect to your data sources, clean and preprocess your documents, and prepare them for model development — all within your environment. Your data never leaves your infrastructure.
Model Development
We design and fine-tune compact models for your specific classification and extraction tasks. Frontier models accelerate the labeling process; your experts review only the edge cases.
Deployment Engineering
We export your model as ONNX and deploy it on your infrastructure — cloud, on-prem, or air-gapped. No runtime API calls back to us. You own the weights, not us.
Production Support
We monitor model performance, retrain as your data evolves, and keep your models accurate at scale. You get a deployed model that stays relevant — not a one-time handoff.
Built for regulated, document-heavy industries.
Every domain has its own vocabulary, risk surface, and compliance requirements. We adapt to yours — and deploys where your security policy demands.
E-discovery relevance, contract classification, and privilege review — at 85% less manual effort.
Clinical document triage, adverse event classification, and prior authorization extraction in HIPAA-compliant environments.
Research relevance filtering, KYC document review, and regulatory filing classification at a fraction of frontier API cost.
Intelligence report categorization and FOIA triage deployed on air-gapped infrastructure where commercial APIs can't reach.
From conversation to deployed model — we handle it all.
Tell us what you need. We design, build, deploy, and maintain your custom model on infrastructure you control. No PhD required on your side.
Tell us what you need
We'll learn about your data, your infrastructure, and the tasks you want to automate. Then we design a solution — model architecture, deployment target, and a timeline.
We build your model
We connect your data sources, use frontier models to accelerate labeling, fine-tune a compact model for your task, and export it as ONNX — ready to deploy.
We deploy on your infra
We deploy the model on your infrastructure — cloud, on-prem, or air-gapped — and integrate it into your workflows. No runtime API calls to us. Your data stays put.
We keep it running
We monitor accuracy, retrain as your data changes, and optimize performance over time. A model that starts accurate stays accurate.
Common questions about custom AI deployment.
Everything you need to know about how Beag Labs builds, deploys, and maintains small models for regulated and data-sensitive environments.
What is Beag Labs?
Beag Labs is an AI services company that builds and deploys custom small language models for regulated, data-sensitive organizations. We handle everything — data pipeline engineering, model development, ONNX export, and deployment on your infrastructure. You own the trained model weights and your data never leaves your environment.
How does your engagement model work?
We start by understanding your data, infrastructure, and the tasks you want to automate. We design a solution, build a custom model using frontier models to accelerate labeling, and deploy it on your infrastructure — cloud, on-prem, or air-gapped. After deployment, we monitor performance and retrain as your data evolves.
Can you deploy on-premises or in air-gapped environments?
Yes. Every model we build is exported as ONNX and deployed on infrastructure you control — cloud, on-premises, or fully air-gapped. There are no runtime API calls back to us. Your inference data never leaves your environment, and you own the model weights outright.
Do you train on our data or share it with third parties?
No. We never train foundation models on your data, and your data never leaves your environment during inference. The custom models we build for you are yours alone — not absorbed into a shared model. Data connectors operate within your environment, and we never touch your production data.
What types of models do you build?
We build compact classification, extraction, and relevance models for regulated industries: compliance (NIST 800-53 control classification), security (CVE, OWASP, MITRE ATT&CK mapping), legal (e-discovery, contract clause extraction), and healthcare (clinical document triage, adverse event classification). Each model is typically 500M to 5B parameters.
How is Beag Labs different from calling an LLM API like OpenAI or Anthropic?
API providers charge per-token for every inference, your data passes through their servers, and you're locked into their platform. We build a compact model you own and deploy on your own hardware — no per-token costs, no data exposure, no vendor lock-in. At scale it can be up to 13x cheaper than per-token API pricing.
How long does it take to get a deployed model?
From our first conversation to a deployed model typically takes under two weeks. We use frontier models to accelerate the labeling pipeline, then fine-tune and export as ONNX for deployment on your infrastructure. Ongoing support keeps the model accurate as your data evolves.
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