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. 87% of inference drifts from domain truth without fine-tuning.
LLMs forget everything outside a context window. 1M+ tokens of institutional knowledge lost between sessions.
Your SOPs, products, and internal data live in your systems. 0% of your proprietary knowledge exists in the base weights.
23% hallucination rate on domain queries. Inconsistency and latency at scale. Base models are research artifacts, not infrastructure.
100+ 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. Total isolation.
Langtrain combines the zero-ops convenience of Hosted APIs with the data privacy and weight ownership of building it yourself.
See how teams are using Langtrain to turn generic open-source models into specialized domain experts that drive actual business value.
Base models hallucinate policies and give generic answers.
Fine-tune on your closed-won Zendesk tickets and internal wikis.
92% resolution rate without human intervention, zero hallucinated refund policies.
Copilot doesn't understand your proprietary monorepo architecture.
Fine-tune DeepSeek Coder on your GitHub repos and PR comments.
40% reduction in PR review cycles, instant onboarding for new engineers.
General models fail at highly specialized medical/legal reasoning.
Inject domain-specific PDFs and case laws into Llama 3 weights.
Passes specialized board exams with 15% higher accuracy than base models.
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.
