Internacious is an AI Infrastructure & Integration Specialist, with 20 years of reliable, secure, and scalable infrastructure client success stories.
Now we're one of the early movers advising how AI solutions are built.
Transform Your IT Infrastructure into AI Infrastructure
If AI will mandate absolutely all organisations to re-imagine, re-invent, and re-build on AI technologies, then your IT Infrastructure has just become AI Infrastructure.
AI models are becoming as foundational to business technology as servers, networks, and storage have been traditionally. Rather than just applications running on your IT infrastructure, models are becoming part of the core infrastructure that your business builds upon.
Our AI Infrastructure Services
LLMOps / MLOps as a Service
DevOps for AI. We help organizations manage the lifecycle of their AI models through:
Deployment & Hosting
Setting up secure, scalable environments to run models (on-prem GPUs, private cloud instances in AWS/Azure/GCP, or using serverless GPU platforms)
Monitoring & Observability
Traditional monitoring checks CPU and RAM. AI monitoring checks for model drift, response quality, hallucination rates, token usage, and cost
Model & Prompt Versioning
Just like code, prompts and models need to be versioned, tested, and rolled back if necessary
Private & Hybrid AI Deployments
Many organizations cannot send their sensitive data to a public API like OpenAI's. We help you:
Deploy Open-Source Models
Set up and fine-tune powerful open-source models on your business's private infrastructure
Architect Secure Data Flows
Ensure that sensitive data is processed on-prem or in a private cloud, while non-sensitive queries can still leverage more powerful public models, creating a secure hybrid architecture
Data Pipeline & Vector Database Management
- •Setting up, securing, and scaling vector databases (Pinecone, Chroma, Weaviate)
- •Building data ingestion pipelines that automatically chunk, embed, and index new information
AI Readiness Assessment
Services to assess your current infrastructure, data maturity, and security posture to determine how ready you are to adopt AI. We provide a strategic roadmap tailored to your business needs.
Technology Stack Selection
We guide you through the complex and rapidly changing AI ecosystem. Which model should you use? Which vector database is best for your use case? Which hosting platform offers the best price-performance?
Cost Optimisation for AI
AI can be incredibly expensive. We help you manage and predict costs by optimizing token usage, choosing the right models for different tasks, and implementing cost monitoring dashboards.
AI Security & Governance
- •Preventing Prompt Injection: Securing AI agents from malicious user inputs
- •Data Leakage Prevention: Ensuring the AI doesn't expose sensitive information
- •Access Control: Defining who can use which AI tools and on what data
LLMs are the New Infrastructure
This is not just an incremental change but a fundamental shift in how technology is built and programmed. AI as a truly new layer of infrastructure changes how computers are programmed, and the entire technology stack that surrounds it.
LLMs are having this effect by introducing different requirements for memory and latency, which forces a re-evaluation of how software and infrastructure are developed.
Impact on a Foundational Level
The development and operation of these models are driving the creation of new kinds of datacentres and specialized chips. This demonstrates that the impact of models is being felt at the very foundation of hardware infrastructure.
Shift in Application Logic
Traditionally, programmers explicitly coded the logic of an application. With the advent of models, there is a significant shift where applications now ask the models to "come up with the answer." This delegation of logic is a core reason why models are considered a new and fundamental piece of infrastructure - consequently, Models require a "blank sheet of paper" approach.
Core Service Components
Deployment Orchestration
Automate model deployment across hybrid environments (cloud/on-prem/edge).
Deliverables: CI/CD pipelines (Kubeflow, MLflow), containerization (Docker/K8s), Terraform/IaC scripts.
Real-time Monitoring
Track model performance, data drift, and resource utilization.
Deliverables: Custom dashboards (Grafana/Prometheus), alerting systems, drift detection algorithms.
Version Control & Rollback
Manage model iterations with audit trails.
Deliverables: Model registry (MLflow, DVC), automated rollback protocols, lineage tracking.
Lifecycle Automation
Handle retraining, validation, and retirement.
Deliverables: Scheduled retraining workflows, A/B testing frameworks, sunset policies.
Compliance & Security
Ensure governance and data protection.
Deliverables: Model vulnerability scans, bias detection reports, audit logs for regulations (GDPR, HIPAA).
Key Differentiators
Hybrid Expertise
Unique ability to deploy models across on-prem GPU clusters + cloud
Legacy Integration
Connect MLOps to existing ITSM tools (ServiceNow, Jira) for change management
Business Integration
Bridging AI capabilities with business-critical systems
Your Strategic Roadmap
Internacious offers AI Services packages to get you started on your AI journey, including:
"AI Readiness Assessment"
"Private Chatbot Deployment"
"LLMOps Starter Package"
Ready to Transform Your Infrastructure?
Contact us today to schedule a consultation and learn how Internacious can help you leverage AI as part of your core infrastructure.
Contact Us
Let's talk about your business.