The infrastructure foundation that runs modern AI models securely and efficiently — on-premise or in your private cloud. Core-AI designs and deploys the GPU servers and supporting systems that make private AI viable at firm scale.
What We Build #
Running modern AI models in production requires more than dropping a model behind an API. It requires the right hardware sizing, an efficient inference layer, and a way to route requests, manage models, and integrate with your existing applications.
Core-AI builds this stack end-to-end for firms that need full sovereignty over their AI compute — Québec law firms first, and any practice where sending client files to a third-party API is not an option.
Infrastructure Components #
- AI Model Servers — High-performance inference servers for local models, sized to your throughput and latency targets. NVIDIA H100/A100/L40S or equivalent.
- Optimized Inference Layer — Tuned for your model and traffic profile, including quantization where appropriate.
- Private Data Layer — A private index and document store sized for your corpus and query volume.
- Orchestration & Routing — Manage multiple models, fallback chains, rate limiting, and request routing across hybrid deployments.
- Observability & Monitoring — Logs, traces, GPU utilization, throughput, and model accuracy drift.
- Security & Compliance — Network isolation, audit logging, role-scoped access, and integration with your existing identity system.
System Architecture #
Users
Gateway
Services
Local Models
Data Systems
Deployment Models We Support #
- Fully on-premise — Your data center, your GPUs, your network. We deploy and you operate.
- Private cloud (VPC) — Dedicated infrastructure in AWS, Azure, GCP, or OVH — fully isolated from public AI APIs.
- Hybrid — Sensitive workloads run on-prem; non-sensitive or burst capacity routes to commercial APIs through a policy-controlled gateway.
- Air-gapped — For the most security-sensitive environments where the AI cluster has no external network access at all.
Why Run Private AI Infrastructure #
- Data sovereignty — No queries, embeddings, or documents ever leave your network.
- Predictable cost — Fixed infrastructure cost replaces per-token API billing at scale.
- No vendor lock-in — Models can be swapped or replaced without rewriting your stack.
- Compliance — Keep personal information inside Quebec, which removes the cross-border transfer question Law 25 and PIPEDA would otherwise force you to answer. GDPR, PCI-DSS, and client-imposed rules are handled the same way: the data never goes anywhere.
Related Services #
- Enterprise AI Chatbots — built to run on the infrastructure we deploy.
- AI Agents — run on the orchestration layer described above.
- Document Intelligence — the search pipeline that lives on this data layer.
Frequently Asked Questions #
What GPU hardware do you recommend for running AI models on-premise?
It depends on the model size and throughput requirements. For most firm-scale workloads, we recommend NVIDIA L40S or A100 GPUs. For the largest models or highest throughput, H100s are ideal. We conduct a hardware sizing exercise during Design and provide a bill of materials so you can procure or validate your existing inventory.
Can you deploy on our existing servers, or do we need new hardware?
We assess your existing hardware first. Many organizations have underutilized GPU-capable servers that can run smaller models efficiently. Where new hardware is required, we size it precisely — we do not over-engineer. We also support private cloud deployments (AWS, Azure, GCP, OVH) if on-premise procurement is not viable.
How does on-premise AI infrastructure cost compare to commercial API billing?
At moderate-to-high usage, on-premise infrastructure becomes significantly cheaper than per-query API billing once hardware is amortized. We provide a cost model during Discovery so you can build a business case before committing.
Do you support air-gapped environments with no external internet access?
Yes. Air-gapped deployments are a speciality. All models, the private data layer, and orchestration components are packaged for offline installation. We have experience deploying in classified, regulated, and high-security environments where no external network connectivity is permitted.