PRITECHKSUPPORTStart a conversation

Pritechk Support  /  AI Factory

Enterprise AI built to operate

From model to
production system.

We design and deploy the full AI production environment—on-premises, sovereign, hybrid or cloud—and enable your teams to run it.

Discuss your priority →Explore the practice ↓
BUILD / OPERATING SYSTEMFDE / ACTIVE
Control coreAI FACTORY01 / 06
DataComputeModelsOperations
DesignOperateImprove
DeploymentOn-prem / hybrid / cloud
WorkloadsML / GenAI / agents
OutcomeRepeatable production AI

Six focused capabilities

The complete production stack.

Technology-independent design, with NVIDIA DGX/HGX-class options where workload, sovereignty and economics justify them.

01

Workload & platform strategy

Size use cases, models, latency, data locality and economics before choosing infrastructure.

Output / Platform decision
02

On-prem & sovereign AI

Design DGX/HGX-class compute, high-speed fabric, storage and secure single-tenant environments.

Output / Reference architecture
03

Data, RAG & agent foundations

Build governed data pipelines, retrieval, tool integration and reusable agent patterns.

Output / AI foundation
04

Model engineering & inference

Select, fine-tune, evaluate, optimise and serve predictive and foundation models.

Output / Production model
05

MLOps, LLMOps & orchestration

Automate release, evaluation and rollback with Kubernetes, registries and delivery pipelines.

Output / Delivery platform
06

Observability, security & FinOps

Operate capacity, performance, safety, cost and incidents as one production discipline.

Output / Operating model

FDE delivery path

Design once. Deliver repeatedly.

An FDE-led path from workload evidence to an operable AI platform.

01

Discover

Profile workloads, data, risk and economics.

02

Architect

Design compute, network, storage and software.

03

Build

Deploy the platform and reusable foundations.

04

Prove

Benchmark models, inference and operating controls.

05

Operate

Transfer ownership and continuously optimise.

What you leave with

Capability your teams can operate.

01AI factory target architectureCompute / network / storage / software
02Production model and agent platformServing / RAG / tools / evaluation
03MLOps and LLMOps delivery systemCI/CD/CT / registry / rollback
04Operations and capacity modelSRE / security / FinOps / transfer

Start with the right decision

Where should your AI run?

Let’s choose the right production model and build a factory your teams can operate.

Start a conversation ↗