Access Anywhere
Every interface.
One model.
Native desktop apps, CLI, Python, and TypeScript — access your custom model however your team builds.
Inject your proprietary data into open-source LLMs and deploy production-grade intelligence through CLI, SDKs, or Mac App — in minutes.
Without fine-tuning, every model you deploy is a stranger to your business.
Public models were trained on the internet — not your business. Every inference drifts further from your domain.
LLMs forget everything outside a context window. No institutional knowledge survives between sessions.
Your SOPs, products, and internal data live in your systems. Base models have never seen them.
Hallucinations, inconsistency, and latency at scale. Base models are research artifacts, not infrastructure.
50+ open-source models.
Pick any base model. We handle quantization, adapter merging, and format conversion.
LoRA & QLoRA
Configurable rank, epochs, learning rate. No PyTorch.
Safety by default.
PII, profanity, regex rules, custom classifiers — enforced at inference.
One command.
Managed endpoint, private VPC, or export to GGUF / ONNX.
Meets you where you work.
GUI, CLI, SDK, or raw HTTP — same underlying platform.
Measure what matters.
Run benchmark evals and compare your fine-tuned model against the base before shipping.
Your weights.
Your infra.
On-premise mode, private VPC deployment, zero telemetry on training data. SOC2 compliant.
Native desktop apps, CLI, Python, and TypeScript — access your custom model however your team builds.
Turn open-source models into production-grade domain intelligence — without giving up your weights, your data, or your autonomy.
Joined by developers at Anthropic, Hugging Face, Cohere & more
