LLMaaS: Sovereign Large Language Model as a Service
RackCorp.ai LLMaaS provides private, sovereign, enterprise-grade Large Language Model inference infrastructure, delivered as a hosted service with full control over data location, model choice, cost structure, and update cadence.
Designed for organisations that require AI capabilities without exposing sensitive data to public LLM platforms or losing control over governance, compliance, and performance. Your data never leaves your chosen region and is never used for training or shared with other customers.
LLMaaS - Sovereign AI Infrastructure
Data Sovereignty
Explicit physical data location visibility with regionally isolated processing. Your data never leaves your chosen region and is contractually protected from being used for training or shared with other customers.
OpenAI-Compatible API
Drop-in replacement for OpenAI APIs with seamless integration. Simply replace api.openai.com with your RackCorp.ai endpoint - no code changes required.
Model Flexibility
Support for LLaMA, Mistral, Gemma, and Bring Your Own (BYO) models. Run specific versions indefinitely with controlled upgrades and rollback capabilities.
Enterprise Control
Full control over model updates, version changes, and rollback. Custom pricing plans, no vendor lock-in, and models can be swapped without application changes.
Sovereign AI Infrastructure
Private, hosted LLM inference infrastructure with regionally isolated processing and dedicated, isolated data processing per client. Your data is contractually protected and never used for training or shared.
Hybrid Deployment
Use both public and private LLMs, selecting the right model for each workload. Route sensitive data to sovereign LLMs while using public LLMs for non-sensitive tasks.
Data Protection
Contractual guarantee that your data is never used for model training, never shared with other customers, and never leaves your chosen region without your explicit consent.
Predictable Costs
Transparent, controllable cost structure with custom pricing plans at scale. Avoid per-query pricing volatility and currency exchange risks.
Regional Performance
Predictable latency via regional inference with no intra-country or international latency penalties. Data processed entirely within your selected region.
No Vendor Lock-In
Open standards and full portability. Models can be swapped without application changes, and your infrastructure is fully portable across NVIDIA-backed environments.
Key Benefits
Data Sovereignty
Explicit physical data location visibility with regionally isolated processing. Your data never leaves your chosen region and is contractually protected from being used for training or shared with other customers.
Data Protection Guarantee
Contractual guarantee that customer data is never ingested or learned from by models, never exposed to other customers or competitors, and never used for third-party training.
OpenAI Compatibility
Drop-in replacement for OpenAI APIs - simply replace the endpoint URL. No workflow or application logic changes required, ensuring seamless integration with existing systems.
Model Control
Full control over model versions, updates, and rollback. Run specific versions indefinitely with controlled upgrade paths and testing before deployment.
Predictable Performance
Predictable latency via regional inference with no contention-driven performance issues. Consistent performance without the unpredictability of shared public platforms.
Cost Transparency
Transparent, controllable cost structure with custom pricing plans at scale. Avoid per-query pricing volatility and currency exchange risks associated with public platforms.
Technical Specifications
| Service Type | Large Language Model as a Service (LLMaaS) |
| API Compatibility | OpenAI-compatible API (drop-in replacement) |
| Supported Models | LLaMA (1-4), Mistral, Gemma, BYO (Hugging Face models) |
| Data Sovereignty | Explicit physical data location, regionally isolated processing |
| Data Protection | Contractual non-use of data for training, isolated per-client processing |
| Infrastructure | GPU-backed inference nodes, load-balanced, highly available |
| Access | HTTPS over Internet or private networks |
| Model Governance | Version control, testing, rollout, rollback capabilities |
| Portability | Fully portable across NVIDIA-backed environments |
| Integration | OpenAI-compatible API, standards-compliant |
Use cases
Sensitive Data Processing
Process sensitive and regulated data with sovereign AI infrastructure, ensuring data never leaves your region and is contractually protected from being used for training.
- Process sensitive data securely
- Meet regulatory compliance requirements
- Data sovereignty guaranteed
- No data exposure to third parties
Internal Knowledge Assistants
Deploy internal knowledge assistants that process proprietary information with guaranteed data protection and no risk of data leakage to public models or competitors.
- Secure internal knowledge access
- Protected proprietary information
- No data training risk
- Internal data remains internal
Voice and Phone AI Assistants
Power voice and phone-based AI assistants with predictable latency and regional processing, ensuring optimal performance and data sovereignty for customer interactions.
- Low-latency voice processing
- Regional inference for performance
- Protected customer data
- Consistent performance
Workflow Automation
Integrate LLM capabilities into workflow automation tools like n8n, processing sensitive business data with guaranteed data protection and sovereign infrastructure.
- Automated workflow processing
- Sensitive data protection
- Seamless tool integration
- Standards-compliant APIs
Document Analysis
Analyze and summarize documents containing sensitive information with sovereign AI, ensuring documents never leave your region and are never used for training.
- Secure document processing
- Protected sensitive content
- No data retention for training
- Compliance-ready processing
High-Volume Workloads
Handle high-volume AI workloads with predictable costs and performance, avoiding per-query pricing volatility and contention-driven performance issues.
- Cost-effective at scale
- Predictable performance
- Custom pricing plans
- No contention issues
How it works
Choose Region & Model
Select your data processing region and choose from supported models (LLaMA, Mistral, Gemma) or bring your own model. Configure data sovereignty and isolation requirements.
Get API Endpoint
Receive your OpenAI-compatible API endpoint. Simply replace api.openai.com with your RackCorp.ai endpoint in existing applications - no code changes required.
Process Data Securely
Send requests to your sovereign LLM endpoint. Data is processed entirely within your chosen region, never leaves the network boundary, and is contractually protected.
Control & Scale
Control model versions, updates, and rollback. Scale resources as needed with predictable costs and performance, maintaining full control over your AI infrastructure.
Frequently Asked Questions
What is LLMaaS?
LLMaaS (Large Language Model as a Service) provides private, sovereign, enterprise-grade Large Language Model inference infrastructure, delivered as a hosted service with full control over data location, model choice, cost structure, and update cadence.
RackCorp.ai LLMaaS is designed for organisations that require AI capabilities without exposing sensitive data to public LLM platforms or losing control over governance, compliance, and performance. Your data is contractually protected and never used for training or shared with other customers.
Why LLMaaS Exists
The Problem with Public LLM Platforms
Public LLM platforms introduce several enterprise risks:
Data Sovereignty & Compliance Risks
- Uncertainty about where data is physically processed
- Risk of data being ingested or learned from by public models
- Potential exposure to other customers or competitors
- Difficulty meeting in-country processing and regulatory requirements
Lack of Control
- No control over model updates, version changes, or rollback
- Updates occur on vendor timelines (often US-centric)
- Behaviour changes without notice
Cost & Performance Issues
- Per-query pricing scales poorly at high volume
- Currency exchange volatility (e.g. USD vs local currencies)
- Contention-driven latency and unpredictable performance
- “Cheap per query” becomes expensive at scale
The Enterprise Reality
Enterprises require AI that:
- Fits existing governance models
- Offers predictable cost modelling
- Integrates with existing systems
- Does not force a “cloud-at-all-costs” mindset
- Protects sensitive data from being used for training
- Ensures data sovereignty and compliance
What RackCorp.ai LLMaaS Provides
Core Capabilities
- Private, hosted LLM inference infrastructure
- Regionally isolated processing - data never leaves your chosen region
- Dedicated, isolated data processing per client
- Contractual guarantee - customer data never used for training
- Customer-specific billing and pricing models
- OpenAI-compatible API for seamless integration
- Support for open-source and customer-supplied models
- Explicit physical data location visibility (not just “in-country” claims)
Enterprise Control
- Version control, testing, rollout, and rollback
- Custom pricing plans at scale
- No vendor lock-in
- Models can be swapped without application changes
- Full data sovereignty and compliance alignment
Data Sovereignty & Protection
Your Data is Protected
Contractual Guarantees:
- Never used for training: Your data is contractually protected from being ingested or learned from by models
- Never shared: Your data is never exposed to other customers or competitors
- Never leaves your region: Data is processed entirely within your selected region
- Isolated processing: Dedicated, isolated data processing per client
Explicit Location Control:
- Choose the explicit physical data location
- Regionally isolated processing
- Data never leaves the defined network boundary
- Transparent data location visibility
Compliance Ready
- Meet in-country processing requirements
- Align with data sovereignty regulations
- Support regulatory compliance needs
- Contractual data protection guarantees
Supported Models
LLaMA (1-4) - Meta
- Deep reasoning capabilities
- Large datasets support
- Fine-tunable for custom use cases
- Enterprise-grade performance
Mistral
- High efficiency and performance
- Excellent price/performance ratio
- Mid-sized datasets optimization
- Fast inference capabilities
Gemma - Google
- Lightweight and fast
- Ideal for:
- Chat applications
- Categorisation tasks
- Summarisation
- Latency-sensitive workloads
Bring Your Own (BYO) Model
- Any Hugging Face-supported model (hardware permitting)
- Custom and fine-tuned models
- Full model portability
- Flexible deployment options
OpenAI Compatibility
Drop-in Replacement
RackCorp.ai LLMaaS provides an OpenAI-compatible API that is a drop-in replacement for OpenAI services:
Simply replace:
api.openai.com → your-endpoint.rackcorp.ai
No code changes required:
- Existing applications work immediately
- No workflow changes needed
- No application logic changes
- Standards-compliant API
Integration Examples
Automation Tools:
- n8n workflows redirected to RackCorp.ai LLMaaS
- Existing OpenAI integrations work seamlessly
- Sensitive data remains internal
- Full interchangeability demonstrated
Applications:
- Replace OpenAI endpoints in existing code
- Use standard OpenAI SDKs and libraries
- Maintain existing application architecture
- Seamless migration path
Public LLMs vs RackCorp.ai LLMaaS
When to Use Public LLMs
Public LLMs excel at:
- Creative tasks and ideation
- Exploration and experimentation
- Internet-scale knowledge requirements
- Non-sensitive data processing
- Rapid iteration and feature releases
When to Use RackCorp.ai LLMaaS
RackCorp.ai LLMaaS excels at:
- Sensitive data processing
- Regulated workloads requiring compliance
- Data sovereignty requirements
- Predictable latency via regional inference
- Cost-sensitive high-volume workloads
- Model consistency requirements
- Enterprise governance alignment
Hybrid Deployment Model
Organisations can use both public and private LLMs, selecting the right model for each workload:
Public LLMs for:
- Ideation and creative tasks
- Non-sensitive data
- Experimental use cases
- Internet-scale knowledge
RackCorp.ai LLMaaS for:
- Sensitive data
- Regulated workloads
- Latency-critical applications
- Cost-sensitive high-volume workloads
Coming Soon: Dynamic routing between public and private LLMs (planned mid-January 2026)
Enterprise Use Cases
Internal Knowledge Assistants
Deploy internal knowledge assistants that process proprietary information with guaranteed data protection and no risk of data leakage.
Voice and Phone AI Assistants
Power voice and phone-based AI assistants with predictable latency and regional processing for optimal customer interactions.
Workflow Classification and Routing
Integrate LLM capabilities into workflow automation, processing sensitive business data with guaranteed data protection.
Document Summarisation and Analysis
Analyze and summarize documents containing sensitive information with sovereign AI, ensuring documents never leave your region.
AI Chat Interfaces
Deploy AI chat interfaces (e.g. Katonic AI Chat UI) with sovereign infrastructure, protecting customer conversations and data.
Custom Application Workflows
Integrate LLM capabilities into custom applications with OpenAI-compatible APIs, maintaining data sovereignty and compliance.
Getting Started
Getting started with RackCorp.ai LLMaaS is simple:
- Choose Region: Select your data processing region
- Select Model: Choose from supported models or bring your own
- Get Endpoint: Receive your OpenAI-compatible API endpoint
- Integrate: Replace OpenAI endpoints in your applications
Our team is here to help you get started. Contact us today to learn how RackCorp.ai LLMaaS can provide sovereign AI infrastructure for your organization.
Get Started Today
Ready to experience enterprise-grade cloud infrastructure? Start with our free trial or contact our sales team for a custom solution.