$ 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.

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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.

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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.

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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.

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