Lepton AI
Build and deploy high-performance AI applications at scale with zero infrastructure management.
The open-source AI-Native operating environment for enterprise liquid software development.
LSD (Liquid Stack Distribution) is a comprehensive AI-native infrastructure platform designed to bridge the gap between traditional Kubernetes environments and the demanding requirements of Large Language Model (LLM) orchestration. By 2026, LSD has positioned itself as the definitive 'Liquid Software' layer, enabling seamless portability of AI workloads across hybrid-cloud environments. The technical architecture centers on the LSD Navigator, an intelligent abstraction layer that manages GPU slicing, persistent storage for vector databases, and automated model deployment pipelines. Unlike standard container platforms, LSD is optimized for the 'Liquid' lifecycle, where code and data are continuously refined. It integrates deeply with tools like Prometheus and Grafana for AI-specific observability, providing telemetry on token usage, inference latency, and hardware efficiency. For organizations scaling from R&D to production, LSD provides the pre-configured security hardening (DevSecOps) and networking policies required to run sovereign AI models without the overhead of building a stack from scratch.
A centralized graphical dashboard for managing multi-cluster AI resources.
Build and deploy high-performance AI applications at scale with zero infrastructure management.
The search foundation for multimodal AI and RAG applications.
Accelerating the journey from frontier AI research to hardware-optimized production scale.
The Enterprise-Grade RAG Pipeline for Seamless Unstructured Data Synchronization.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Dynamic scaling of inference pods based on real-time token-per-second demand.
Custom Grafana dashboards pre-configured for GPU temperature, memory, and model drift.
Leverages NVIDIA MIG and fractional GPU technology to share hardware across small models.
Encrypted model storage and key management for running sensitive LLMs locally.
Scaling a custom Llama-3 instance across multiple departments securely.
Registry Updated:2/7/2026
High AWS/Azure costs due to idle GPU instances.
Training on-prem for security but bursting to cloud for power.