Local LLM Advisory

Get the Right AI Hardware.
The First Time.

Expert guidance on choosing hardware for local LLMs. Avoid costly mistakes in GPU selection, memory sizing, and model compatibility.

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20 years in enterprise technology · Former Head of Strategy, British Telecom · LinkedIn Profile →

Local LLM Hardware Is Complex

Most teams waste thousands on wrong configurations because benchmarks don't tell the whole story.

Costly Mistakes

Mac Studio, NVIDIA GPUs, cloud credits. Wrong choices mean thousands burned and weeks of rework.

Hidden Constraints

That 128k context model won't fit in 64GB RAM at production quality. Benchmarks rarely show real-world limits.

Integration Gaps

Many local models claim function calling but fail on real agent workflows. You won't know until you've committed.

Advisory Packages

Three ways to get certainty before you invest.

Tier 1
Hardware Audit
£750 – £1,500
  • 60–90 minute consultation
  • Use case analysis
  • Memory and context review
  • Budget optimization
  • Written recommendation
Request Consultation
Tier 3
Setup & Handover
£6,000 – £12,000
  • Full implementation support
  • RunPod / Mac Studio / DGX
  • Production-ready deployment
  • IDE integration (Continue.dev)
  • Monitoring configuration
  • Upgrade path documentation
Discuss Requirements

Built on Experience

20
Years in enterprise technology
50+
AI implementations advised
£2M+
Client savings from right-first decisions

Who This Serves

Technical leaders who need local inference but lack specialized ML infrastructure expertise.

CTOs at system integrators
Technical founders (Seed–Series A)
AI agency technical leads
Privacy-regulated startups
R&D innovation teams
Enterprise architects

Ready to Get It Right?

One conversation can save months of trial and error.

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