What an AI company’s infrastructure needs
An AI company’s infrastructure looks nothing like a SaaS startup’s, and that difference runs through procurement, security and compliance alike.
Your ML engineers need GPU capacity that appears on demand. Your training data needs real encryption. Your investors ask about SOC 2. Your enterprise prospects ask about ISO 42001. And the EU AI Act added obligations that did not exist two years ago.
We run the infrastructure underneath all of that, so your team builds models instead of managing servers.
GPU capacity when the training run needs it
The single biggest infrastructure challenge for AI startups is compute. Training runs that require hundreds of GPU-hours cannot wait for procurement cycles, and inference endpoints that serve millions of requests need reliable, low-latency infrastructure.
We manage GPU compute across every major cloud provider — AWS, Azure, GCP, CoreWeave, Lambda, and specialist GPU hosting platforms. Our approach optimises three dimensions simultaneously: cost (ensuring you are on the right instance type and pricing model), availability (reserving capacity for critical training windows), and performance (matching hardware to workload characteristics).
When your Series A closes and you need to 10x your training capacity, we scale your infrastructure in days, not weeks.
The assets that are actually your company
AI startups face a unique security surface. Your valuable assets are not just customer data — they are training datasets, model weights, fine-tuning data, and inference APIs. A breach that exposes model weights or proprietary training data can destroy your competitive advantage overnight.
Our AI security approach covers the entire pipeline: data ingestion encryption, secure training environments with access logging, model weight protection through hardware security modules and encrypted storage, and inference endpoint hardening with rate limiting and authentication. We implement data lineage tracking so you know exactly where every training sample originated and who has accessed your models.
Clear the AI governance questions before a buyer asks them
The regulatory landscape for AI has transformed. The EU AI Act is now in force, with obligations ranging from transparency requirements for general-purpose AI to strict compliance frameworks for high-risk systems. ISO 42001 has emerged as the international standard for AI management systems. And enterprise buyers increasingly require evidence of responsible AI practices before signing contracts.
We help you navigate this landscape pragmatically. Our compliance programmes cover risk classification under the EU AI Act, ISO 42001 readiness, NIST AI Risk Management Framework alignment, and SOC 2 Type II certification. We build the governance infrastructure — policies, technical controls, audit trails, and bias monitoring systems — that satisfies regulators and unlocks enterprise sales.
Moving models from notebook to production
The gap between a model that works in a Jupyter notebook and one that serves production traffic reliably is enormous. Most AI startups hit this wall around Series A, when the pressure to ship production features outpaces the team’s ability to maintain infrastructure.
We build and manage MLOps infrastructure that bridges this gap: experiment tracking, model registries, CI/CD pipelines for model deployment, A/B testing frameworks, monitoring and alerting for model drift, and automated rollback when performance degrades. Your engineers ship models. We make sure those models run reliably in production.
Expect these three things from us
AI infrastructure is a deliberate specialisation for us, and it shows up in three practical ways.
- Our engineers know the difference between a training workload and an inference workload, and provision each accordingly
- We can explain to your auditor why a GPU cluster needs different controls to a web application
- You get a consistent team that keeps the technical context as the company grows
If you would like to talk any of this through, book a call.
Need London IT support across all of this? See our overview of IT support in London — pricing, compliance posture, and FAQ in one place.