Zero-token architecture: predictable, flat-rate economics
Enterprise decision engines run thousands of automated background tasks every hour, continuously evaluating constraint boundaries, stress-testing procurement drift and triaging operational anomalies.
No metered costs
With our graph engine on local open-weight runtimes, there is no metered charge for any query, simulation or agent loop.
Unlimited computation
Planners and agents can run exhaustive simulations and explore thousands of what-if branches with no per-token charges or budget caps.
Fixed infrastructure ROI
Compute costs tie to your dedicated hardware (workstations, server racks or private cloud compute), giving predictable CapEx and OpEx modelling.
High-performance private runtimes
JanusKS decouples the reasoning engine from specific cloud providers, supporting enterprise-grade, high-concurrency local runtimes.
vLLM and Triton Inference Server
Engineered for enterprise server clusters and private cloud nodes, with high-throughput PagedAttention memory management and low-latency multi-agent querying.
Ollama and LM Studio runtimes
Optimised for local engineering workstations, rapid offline deployments or field office servers, with direct local socket communication.
Model neutrality and independence
Deploy open-weight models suited to your operational requirements, from compact 8B parameter models for edge devices to 70B+ parameter flagship models for complex multi-variable reasoning.
Native Model Context Protocol over local sockets
Autonomous agent reasoning does not need external network exposure.
Local stdio and IPC transports
Agent tools reach the JanusKS Knowledge Graph using MCP over secure local pipes (standard I/O or inter-process communication), with zero TCP ports exposed externally.
Deterministic knowledge graph RAG
Instead of massive unstructured text piles, the system feeds precise, relationship-validated sub-graphs into the local context window, so compact models work from verified facts.
No data leakage
Prompts and context payloads stay in protected local VRAM and RAM buffers and are cleared immediately after execution.
Zero telemetry and defensible air-gapping
We treat data isolation as a physical engineering standard.
Zero outbound pings
In high-security air-gap mode, all crash telemetry, usage analytics, licence validation pings and external model downloads are disabled.
Offline model and schema packaging
Model weights, software binaries, dependencies and ontology updates arrive as cryptographically signed offline bundles, verified against SHA-256 checksums.
Isolated environment compatibility
Operates across classified defence enclaves, secure offshore installations, underground extraction sites and isolated operational technology (OT) segments.
Cloud-tethered AI vs JanusKS local and air-gapped AI
| Evaluation factor | Public cloud AI (OpenAI / Anthropic / hyperscalers) | JanusKS local and air-gapped stack |
|---|---|---|
| Data perimeter | External data centres, shared infrastructure, public network transit. | 100% inside your physical firewall or sovereign private VPC. |
| Ongoing operating cost | Variable, recurring per-token metering. | Fixed hardware cost; unlimited queries, simulations and agent tasks. |
| Network dependency | Needs a continuous, high-bandwidth public internet connection. | Fully functional with zero network connectivity or public access. |
| Model customisation | Constrained to vendor-controlled endpoints, deprecation timelines and rate limits. | Complete control over model weights, quantisations and runtime settings. |
| Auditability and forensics | Opaque black-box models with server-side logging outside your control. | Verifiable, tamper-evident temporal ledgers held exclusively on-premises. |
| Compliance alignment | Subject to cloud shared-responsibility models and foreign jurisdictions. | Designed to support defence, HIPAA, GDPR and sovereign data requirements. |
Hardware and deployment profiles
JanusKS scales across enterprise hardware configurations, from mobile command centres to multi-node data centres.
| Profile | Compute | Scale |
|---|---|---|
| Enterprise data centre (high-throughput operations) | Multi-node NVIDIA Tensor Core clusters (H100, A100, L40S) running vLLM. | Enterprise-wide concurrent scenario planning, multi-user access, real-time IoT graph ingestion and autonomous agent swarms. |
| Site office and regional facility (self-contained unit) | High-density workstation or rack-mounted server with consumer or workstation GPUs (RTX 6000 Ada, RTX 4090). | Independent site coordination, schedule simulation and local contractor compliance tracking with zero external dependency. |
| Mobile field and tactical command (extreme edge) | Ruggedised mobile hardware running quantised open-weight models via Ollama. | Autonomous, single-operator decision support for remote mining, emergency response and defence logistics. |