Frequently asked questions.
Technical and commercial questions about the platform and deployment.
[ Platform ]
Sector88 is building the infrastructure for AI beyond the cloud. It runs in ground stations, air-gapped facilities and other remote or regulated sites.
On each machine, Sector88 runs AI workloads and manages memory across VRAM and system RAM so models fit and stay stable. Across the fleet, it manages every node from one place. We forward-deploy engineers to install, tune, and harden the platform on site.
On the machine, Sector88 is the compute layer on the machine. It sits between your workloads and the hardware, orchestrating memory across VRAM and system RAM to fit models that exceed available VRAM. It exposes an OpenAI-compatible API.
Across the fleet, Sector88 handles model distribution, version control, health monitoring, and orchestration across distributed nodes. This is how you manage tens or hundreds of nodes from one place.
Sector88 treats VRAM and system RAM as one memory hierarchy. Hot layers stay in VRAM for fast execution. Warm layers sit in system RAM, ready for rapid promotion. The scheduler moves data between tiers automatically based on access patterns, context length, and concurrency. The result is that models which would OOM on a baseline engine run successfully with predictable latency.
Language, vision, speech and sensor models. For language models, anything supported by vLLM or llama.cpp. This includes Llama 3, Mistral, Qwen, DeepSeek, Phi, Gemma, Command R, and thousands of HuggingFace models. Both SafeTensors and GGUF quantized formats are supported.
You can also run your own fine-tuned or proprietary models. If the base architecture is supported by the underlying engine, Sector88 will orchestrate it.
Sector88 drives vLLM and llama.cpp, plus a native path. The engine is selected automatically based on hardware profile and model format, or you can pin a specific backend. All engines expose the same OpenAI-compatible API through Sector88.
[ Hardware & Compatibility ]
NVIDIA CUDA (RTX 30/40/50 series, A-series, L-series, H100, H200, Jetson), AMD ROCm (MI250X, MI300X), Intel (Gaudi 2, Gaudi 3, Xeon), Qualcomm Cloud AI, Apple Silicon, and CPU-only deployments. If it can run a supported inference engine, Sector88 runs on it.
Yes. Sector88 supports tensor parallelism across multiple GPUs within a single node, and runs many nodes side by side across a fleet. This is how we run 70B+ parameter models in environments with limited per-node VRAM.
Linux is the primary target. Sector88 ships as a container image (Docker, Podman, Kubernetes) and runs on any distribution with a compatible GPU driver. We test against Ubuntu, RHEL, Rocky Linux, and Alpine. macOS is supported for local development on Apple Silicon.
[ Deployment & Security ]
Yes. Sector88 is purpose-built for air-gapped and sovereign deployments. Zero external dependencies at runtime. Models load from local filesystem or internal registry. Enterprise deployments are built to run fully offline with no outbound network calls.
Community Edition sends one anonymous heartbeat on first run and every 24 hours. The schema includes install UUID, version, OS, architecture, and hardware family. Never prompts, completions, model names, or user identifiers.
Set S88_TELEMETRY=off to disable completely. Pro and Enterprise default to telemetry off. Full schema is published on our security page.
A single-node proof of concept is running in minutes. Full production deployments with forward-deployed engineers, hardening, and integration typically take weeks, not quarters. Timeline depends on fleet size, security requirements, and network topology.
SOC 2 Type II, ISO 27001, and IRAP are actively in progress. We do not claim certifications we have not earned. Our current security posture, data handling practices, and vulnerability disclosure process are documented on the security page.
No. All compute happens locally, inside your perimeter. Prompts, completions, and model weights never leave your environment. There is no cloud relay, no external API dependency, and no data exfiltration path. This is a core architectural guarantee.
[ Engagement & Pricing ]
Pricing is scoped to your environment: hardware mix, fleet size, security requirements, and how deeply our forward-deployed engineers embed with your team. Every engagement receives a written proposal after an initial scoping call. There are no self-serve tiers for production deployments.
Forward-deployed engineers are Sector88 staff who work on site or embedded with your team. They handle infrastructure assessment, installation, integration, tuning, and production hardening. They stay until the platform runs in production and your team can operate it independently.
This is how we work with defence, space, and energy customers where remote access is not possible. Learn more about our process.
Sector88 deployed and configured on site. Forward-deployed engineers who embed with your team. Infrastructure and hardware assessment. Model selection, quantization, and tuning for your workload. Integration with your existing systems. Production hardening, monitoring, and a custom SLA.
Yes. Community Edition is free for individual use and experimentation. It includes a single node with memory orchestration and an OpenAI-compatible API. Pro and Enterprise tiers add the fleet control plane, multi-node support, roles and audit, SLAs, and forward-deployed engineering.
Yes. Most engagements start with a scoped proof of concept at your site. We deploy Sector88 on a representative node, benchmark against your workload, and deliver measured results. Working compute on your site before the contract is signed.
Enterprise engagements include a custom SLA covering response time, uptime targets, and escalation paths. Because Sector88 runs inside your environment, uptime also depends on site power and network. Our SLA covers platform availability, incident response, and engineering support, not the underlying compute.