Platform

S88 Runtime + Hub

Production-grade inference engine and management platform for constrained hardware.

S88 Runtime

Production-grade inference engine that prevents crashes and maximizes utilization on constrained hardware. Intelligent memory orchestration that scales from edge devices to distributed clusters.

$ s88 serve --model llama-70b
[OK] Runtime initialized
→ Server: localhost:8000
→ Metrics: localhost:9090
VRAM: 16.8 GB / 24.0 GB
RAM: 42.3 GB / 64.0 GB
Power: 280W
Status: Serving

Memory Orchestration

Dynamic tiering across VRAM, RAM, and SSD. Predictive prefetch anticipates needs before access. Policy-driven eviction prevents bottlenecks.

Zero Downtime

Never crashes on OOM. Graceful degradation through back-pressure queuing and context clipping. System remains responsive under any load.

Production Telemetry

Built-in Prometheus metrics. Real-time VRAM, RAM, power, and thermal monitoring. Structured event logs for debugging.

Energy-Aware

Adapts to power and thermal conditions. Optimizes workload distribution based on available resources and constraints.

Security-First

Zero prompt logging. Audit-ready telemetry without content exposure. Built for regulated and classified environments.

Drop-In Integration

Works with existing inference engines. Minimal configuration required. Deploy in minutes, not weeks.

S88 Hub Dashboard

S88 Hub

Operational control plane for managing inference deployments at scale. Real-time visibility, performance analysis, and fleet orchestration for production environments.

Real-Time Monitoring

Live visibility into VRAM, RAM, SSD utilization. GPU temperature and power consumption tracking. Performance metrics including throughput and latency.

Performance Analysis

Automated baseline benchmarking. Detailed performance reports and raw data exports. Identifies bottlenecks and optimization opportunities.

Fleet Control

Manage deployments across multiple nodes. Centralized configuration and policy management. Rolling updates and health monitoring.

Web Interface

Browser-based dashboard for visualization and control. Real-time charts and metrics. Model deployment and configuration management.

Enterprise Telemetry

Prometheus integration for existing monitoring stacks. Structured logging for audit trails. SLO tracking and alerting.

Deployment Support

Guided deployment workflows. Configuration validation and testing. Production runbooks and best practices.

Works With Your Stack

Inference engines are built for data centers with unlimited VRAM. Sector88 makes them work everywhere else.

Inference Backends

vLLM, llama.cpp, Triton (and more) provide:

  • Fast inference kernels (PagedAttention, FlashAttention)
  • Continuous batching and scheduling
  • Quantization (INT8, INT4, GGUF)
  • Model serving APIs

Built for data centers. Not designed for constrained hardware, edge deployments, or sovereign infrastructure.

What's Missing

Sector88 adds the operational layer:

  • Compatibility testing and hardware validation
  • Security & compliance defaults
  • Production telemetry and audit trails
  • Air-gapped deployment with offline operation
  • Intelligent memory tiering Upcoming
  • OOM prevention and adaptive offload Upcoming

Use any backend. We add the operational reliability and compliance layer.

Inference engines are optimized for cloud data centers where hardware is abundant and fast. S88 exists because critical AI systems run on edge hardware, air-gapped networks, and constrained infrastructure where reliability is non-negotiable.

Hardware Agnostic

Any GPU, any backend, any model, anywhere.

Hardware Platforms

NVIDIA CUDA
Popular
AMD ROCm
Intel Gaudi / Xeon
Google TPU
Qualcomm AI
Apple Silicon
CPU Servers

Inference Backends

PyTorch Supported
Native inference
vLLM Supported
PagedAttention optimization
llama.cpp Supported
GGUF models, CPU/GPU
TensorRT-LLM Roadmap
NVIDIA optimization
Triton Roadmap
NVIDIA inference server
Ollama Roadmap
Developer tooling

Ready to deploy?

Get access to S88 Runtime and Hub for your infrastructure.

Request Access