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Services

Everything from strategy
to production. One team.

From GPU infrastructure and model selection through to token-level cost optimization — we help any company get more from their AI investment. Whether you need a cost audit, a build partner, or an ongoing operations team, we own the full stack.

GPU to Token OptimizationModel Selection AI Cost AuditLLM Engineering RAG PipelinesFine-tuning MLOpsInference Cost Reduction Model EvaluationManaged Operations DatabricksSnowflake GPU to Token OptimizationModel Selection AI Cost AuditLLM Engineering RAG PipelinesFine-tuning MLOpsInference Cost Reduction Model EvaluationManaged Operations DatabricksSnowflake
01
Advisory

AI Strategy &
Architecture

AI spend is largely invisible until it's out of control. We audit your full stack — from GPU utilization and inference infrastructure down to model choice and token consumption — and identify exactly where cost is being wasted and performance left on the table.

Engagements range from a focused cost and model-selection audit to a full AI architecture review. We give you a clear recommendation with benchmark evidence, not a slide deck full of options.

What you get

GPU-to-token cost audit — where every dollar is going
Model selection with side-by-side benchmark evidence
Build vs. buy vs. fine-tune decision framework
Inference optimization recommendations (batching, quantization, caching)
Infrastructure architecture with full TCO model
Prioritized execution roadmap — what to do next, in order, with costs

Typical engagement

Advisory

2–4 week sprint. Includes discovery workshops, technical deep-dives, and a written architecture decision record (ADR) you own permanently.

Who it's for

Startup to Enterprise

Any company — startup or enterprise — running AI workloads and looking to optimize cost, improve performance, or validate their architecture. Also teams inheriting a stack they didn't build who want an honest second opinion.

Pricing

Fixed-fee engagements. Scope and investment discussed during a free 30-minute discovery call. We don't do T&M for advisory work — you know what you're buying before you sign.

02
Delivery

Build & Delivery
Pods

A dedicated team of AI Architects and LLM Engineers embedded in your delivery rhythm. We scope, sprint, and ship — you own the IP, the code, and the infrastructure.

Pods are structured around your workstream, not ours. One Lead AI Architect, two to four engineers, and a shared Client Success Manager keeping delivery on track.

Capabilities

RAG pipeline architecture and implementation
LLM fine-tuning on proprietary datasets
Model evaluation and benchmark frameworks
Inference optimisation and cost reduction
MLOps: CI/CD, monitoring, retraining pipelines
GPU cluster setup on CoreWeave, Nebius, Lambda Labs

Pod structure

Delivery

1 Lead AI Architect · 2–4 LLM/MLOps Engineers · 1 shared Client Success Manager. Structured around 2-week sprints with weekly founder-to-founder checkpoints.

Engagement model

Retainer

Monthly retainer with defined sprint commitments. Minimum 3-month engagement. Transparent deliverables and exit criteria defined upfront — no open-ended scope.

You own everything

IP Policy

All code, models, pipelines, and infrastructure configurations produced in your engagement are assigned to you on contract signing. No lock-in. No licensing fees.

03
Managed Services

AI Managed
Services

AI isn't a one-time deployment. Models drift. Datasets evolve. New open-source releases outperform your current stack every six months. We keep your AI infrastructure current.

SLA-backed managed services covering everything from model performance monitoring to proactive retraining and infrastructure cost optimisation.

What's included

24/7 model performance and SLA monitoring
Scheduled and triggered model retraining
Inference cost optimisation reviews (quarterly)
New model evaluation against your benchmarks
Monthly performance reports with recommendations
Dedicated Slack channel with 4-hour response SLA

Annual contract

MSP

12-month contracts with quarterly performance reviews. Scope scales up or down based on your deployment footprint. No surprise charges.

SLA commitments

Guaranteed

Agreed uptime and response SLAs defined in your MSA. Breach penalties are real — we stand behind our commitments with financial accountability.

Why managed services

Most AI cost blowouts happen post-launch — model drift, inefficient inference, unmonitored GPU spend. Managed services keep you ahead of that curve instead of reacting to it.

Where most clients start

The two-week
Proof of Concept.

Fixed fee. Your data. Side-by-side benchmarks. A production-ready deployment plan. Most clients sign their first full engagement the week after POC delivery.

1

Discovery & Setup

Collect 200–500 production prompt/response pairs from your existing AI logs. Select model candidates. Design evaluation framework. Stand up infrastructure on your target platform.

2

Benchmark & Deliver

Run side-by-side evaluation. Fine-tune if required. Produce interactive dashboard: accuracy, latency (p50/p95/p99), cost per 1K tokens, full TCO analysis. Deliver production migration plan.

What you walk away with

Live benchmark dashboard — GPT-4 vs. open-source, on your data
Full TCO model: current cost vs. projected cost post-migration
Architecture recommendation with evidence
Production migration plan, phased and costed
Honest assessment — if open-source doesn't win, we'll tell you
Start a POC conversation
Platform Ecosystem

Deeply embedded in
the platforms you already use.

DGX-Ready SI partner. GPU cluster architecture, CUDA optimisation, TensorRT deployment. We speak NVIDIA natively.

H100 / A100TensorRT

Professional Services Partner. MLflow, Unity Catalog, Mosaic AI. LLM fine-tuning and deployment on the Lakehouse.

Mosaic AIMLflow

Partner Connect certified. Cortex AI, Snowpark, vector search. RAG architectures on your existing Snowflake data estate.

Cortex AISnowpark

Enterprise Partner. Open-source model deployment, fine-tuning, and evaluation. Access to the full HF Hub ecosystem.

Inference EndpointsFine-tuning

Delivery partner for GPU cloud. H100 cluster provisioning, Kubernetes orchestration, and cost-optimised inference.

H100 ClustersK8s

Cloud partner for EU and APAC deployments. Cost-effective GPU infrastructure for data-sovereign workloads.

GPU CloudEU / APAC

Not sure which service
you need? Start here.

30-minute call. We'll diagnose what you need — and what you don't.

Book a discovery call Join our team