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ScaleCloud
AI & Generative AI

Operationalise AI with governance

Governed LLM platforms, retrieval-augmented generation, MLOps, and responsible AI — enterprise generative AI that's secure, observable, and measurable.

LLM platforms
RAG
MLOps
Governance
AI security
Responsible AI
AI Compass
LLM Platform
RAG
MLOps
Data
Governance
Security
Observability
Responsible AI
GenAI
1 · AI Decision Framework

AI decisions shape risk and value

Generative AI is powerful but risky. We make platform, data, and governance decisions that deliver value responsibly.

  • RAG grounds models in your data and reduces hallucination risk.
  • Governance and observability are prerequisites, not afterthoughts.
  • Data quality and lineage determine AI quality.
  • Responsible AI protects brand, privacy, and compliance.
GenAI
LLM Platform

Choose and operate foundation models.

3 · Choose the Right Starting Point

Wherever you are on the AI journey

Starting point 1

Exploring GenAI

We design a governed LLM platform with RAG so you move from experimentation to production safely.

What you get
  • LLM platform
  • RAG
  • Governance
4 · AI Reference Architecture

From foundation model to governed GenAI

An AI architecture across eight layers. Select a layer to explore.

Architecture Layers

MLOps

Training, deployment, and monitoring pipelines.

Capabilities
TrainingDeploymentMonitoringVersioning
Supported Cloud Providers — select to see our capability
AWS: Supported with proven delivery patterns and landing-zone expertise.
5 · What We Assess

Six dimensions of AI readiness

A structured assessment of your AI maturity. Select a dimension to explore.

Model strategy

We assess model selection, hosting, and inference strategy for your use cases.

Focus areas
SelectionHostingInference
Model review
6 · AI Deliverables

What you take away

A governed, observable AI platform your teams can build on.

Deliverable 1

AI strategy

Approach, use cases, and roadmap.

7 · Multi-Cloud AI

Architecture first, provider second

We build AI across every cloud model — select an option to see how we approach it.

1 / 5

Public Cloud

Native AI services and managed models.

Key benefits
  • Managed models
  • GPU scale
  • Native services
  • Pay-per-use
Providers we work with
AWS
Microsoft Azure
Google Cloud
OpenAI
NVIDIA
8 · The ScaleCloud AI Journey

Nine steps from use case to governed GenAI

A proven, phased engagement — select a step to see what happens and what you receive.

Step 1Week 1

Discover

Identify use cases and data.

Deliverable
Use case map
9 · Outcomes AI Leaders Need

The outcomes that define success

Six results our AI engagements deliver.

12 · AI & Generative AI FAQs

Answers to common questions

OpenAI, Anthropic, open-source models on Hugging Face, and native models from AWS, Azure, and GCP — chosen per use case and cost.

Operationalising GenAI?

Speak with an AI architect and get a tailored platform design for your use cases.

  • Free 30-minute consultation
  • Vendor-neutral architects
  • NDA available on request
  • No obligation, no pressure
Speak with an Architect

Start your AI engagement

Book a free 30-minute consultation with our AI architects.

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