Features
Native Apple Silicon ML framework (M1-M5)
Zero-allocation MLX bridge
Custom Metal and ANE acceleration paths
TurboQuant KV cache compression (4-6x)
Long-context discontinuous batch serving
Multi-Mac distributed training over Thunderbolt
LoRA/QLoRA/DoRA fine-tuning
Full-parameter pretraining
SFT, GRPO/DAPO, RLKD, distillation
20-workspace terminal TUI
19-screen Tauri desktop GUI
OpenAI/Anthropic-compatible serving API
Model quantization (GGUF, MLX, etc.)
Model merging (SLERP, TIES, DARE, Fisher, RegMean)
Laguna XS.2 model (33B params, 3B active, on-device)
Laguna M.1 model (225B params, 23B active, via API)
256K context length for multi-step reasoning
Multi-agent orchestration with planning and tool use
Sandboxed agent execution environments
Developer surfaces: agents, TUI, IDE extensions, binaries
Custom foundation models deployed on-prem or in VPC
Data connectors to repos, databases, data warehouses
Role-based access control for humans and agents
Executive-grade governance and auditability
On-prem, VPC, and workstation deployment (defense only)
Forward Deployed Research Engineers embed with teams
Real-time observability with end-to-end traces
Air-gapped network support
Open-weight model weights available
