$ Services

Implementation of Meyerbro AI Solutions — delivered through direct, embedded engagements with engineering teams building private, local-first AI. From TensorRT-LLM tuning to SFF Blackwell deployment, Meyerbro AI Labs brings research-grade engineering to your infrastructure.

◆

TensorRT-LLM Optimization

Production tuning of on-premise LLM and SLM workloads on NVIDIA Blackwell and Hopper hardware. Quantisation, kernel selection, request batching, and KV-cache strategies to reduce latency and increase throughput per GPU.

◇

On-Premise SLM Deployment

End-to-end deployment of small language models inside customer-controlled environments. Model selection, hardened runtime, private endpoints, and air-gap-friendly packaging — so sensitive data never leaves the boundary.

◈

High-Density GPU Orchestration

Scheduling, lifecycle management, and observability for dense GPU fleets. Kubernetes device plugins, MIG partitioning, heterogeneous node placement, and graceful failure handling for multi-tenant inference clusters.

▣

Meyerbro Core Implementation

Implementation of Meyerbro AI Solutions built on the Meyerbro Core orchestration layer. Design partner engagements for organisations deploying private AI inside regulated networks.

⚙

AI Platform Engineering

Embedded engineering partnership to build and operate the underlying platform AI workloads run on — Kubernetes, HashiStack, CI/CD, secrets, and observability. Staff-level expertise applied directly to your infrastructure.

🖥

SFF Compute & Edge AI

Design and deployment of small-form-factor AI nodes for branch offices, labs, trading floors, and edge sites. Thermal-aware placement, power budgeting, and integration with centralised fleet management.

📊

AI Observability

Full-stack monitoring for inference workloads: GPU utilisation, token latency distributions, model-level SLOs, cost-per-inference tracking. Built on Prometheus, Grafana, and OpenTelemetry.

📝

Infrastructure as Code

Terraform, Terragrunt, Ansible, and Packer to codify GPU nodes, network fabrics, and orchestration layers. Reproducible, auditable deployments across on-prem, cloud, and hybrid footprints.

$ ready to discuss an implementation?

Connect on LinkedIn to start the conversation.

Get in Touch