Platform

Four layers, all of them yours.

The stack is backend-agnostic. The same deployment targets open inference servers or NVIDIA NIM without a code change, so a model or runtime decision made today is not permanent.

CUSTOMER PREMISES · NO EGRESS 04 · INTERFACE API · CLI · scripted job submission 03 · ORCHESTRATION agent runtime · routing · tool execution 02 · INFERENCE GPU serving · quantised · distributed 01 · GENERATION node-graph pipelines · image · video
Layer 04

Interface

Python API, command line, and scripted job submission. A programmatic control surface for both batch and interactive work.

Layer 03

Orchestration

Containerised agent runtime with task routing and tool execution. Agents plan multi-step work, call tools, and act on the result.

Layer 02

Inference

GPU-accelerated serving with quantised models and distributed inference across heterogeneous nodes on the local network.

Layer 01

Generation

Node-graph pipelines for image and video synthesis with programmatic parameter control and automated rendering.

Deployment tiers

Sized to the workload, not to a catalogue.

Most shops are served by a single workstation-class GPU. Larger corpora and concurrent users scale to multi-GPU nodes or a rack. We specify against measured throughput on your actual jobs rather than a spec sheet.

Tier 01Single workstation GPU
Tier 02Multi-GPU node
Tier 03Rack deployment
RuntimeCUDA · containerised
AccelerationNVIDIA CUDA Every inference path is GPU-accelerated. No CPU-only fallback in production.
ServingQuantised local inference Open-weight models served on premises, sized to the deployment tier.
RoadmapNVIDIA NIM · NeMo Microservice packaging and agent frameworks as deployments scale.
Validated

Distributed inference

A single workload served across multiple nodes on the local network, proving heterogeneous scale-out without reaching for cloud capacity.

Validated

Throughput tuning

Quantised serving and optimised attention kernels tuned for sustained throughput per GPU, so a smaller deployment goes further.

Validated

Containerised agents

Agent runtime deployed in Docker against a local inference server, with no external API dependency anywhere in the path.

Roadmap

From a validated stack to a deployable appliance.

  • Phase 1Complete. Generative core — automated pipelines, optimised inference, distributed serving, validated on production hardware.
  • Phase 2In progress. Agent orchestration — tool-calling runtime, task routing, retrieval over private document stores.
  • Phase 3Vertical workflows — packaged agents for design-to-fabrication and manufacturing intelligence.
  • Phase 4Deployable appliance — reference hardware configurations installed and commissioned as turnkey customer systems.