AI Consulting · Graham Miranda Network

KI-Beratung für praktische Geschäftsworkflows

AI consulting at Graham Miranda is about deciding what NOT to use AI for as much as where to use it. We help you map out which workflows are real wins, which are risk-heavy, and how to govern the ones you ship.

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AI consulting · KI Beratung · AI business workflows · practical AI automation

KI-Beratung für praktische Geschäftsworkflows Graham Miranda service overview

Überblick

Was diese Seite abdeckt

KI-Beratung mit Fokus auf praktische Assistenten, Wissensworkflows, Automatisierungsideen und verantwortliche operative Unterstützung ohne unrealistische Versprechen.

Use-case workshop: which workflows actually benefit from AI
Vendor and model selection (Anthropic, OpenAI, Google, open-weight) with trade-offs
Data governance: residency, training opt-out, retention policy
Cost modelling per workflow with token-budget tracking
Written recommendations including what NOT to automate

So arbeiten wir

Ein transparentes Engagement-Modell mit klaren Meilensteinen.

Workshop

Half-day session with stakeholders to map workflows by AI suitability, risk and current pain.

Recommend

Written recommendations with model choice, governance pattern and cost model per workflow.

Pilot

Optional pilot implementation through Graham Miranda AI automation. Equally happy to hand off to your team.

Ergebnisse, die Sie erwarten können

Praktische, ehrliche Erwartungen — keine übertriebenen Versprechen.

Honest scope

Some workflows simply do not benefit from AI; we will say so.

Right model

Choice based on data sensitivity and cost, not marketing.

Governance

You know who can see what and what happens if outputs are wrong.

Reversible

Recommendations work even if you change vendor later.

Network depth

Häufige Fragen

Kurze Antworten für Besucher, die Graham-Miranda-Servicebereiche vergleichen.

Will AI replace our staff?

For most SMEs no — AI is best at narrow assistance: drafting, searching, summarising. It does not replace judgement.

Which model is best?

Depends on the workflow. Claude is strong for long-context reasoning and writing; GPT-4 / 5 broad capability; Gemini for Google-stack integration; open-weight where data sensitivity demands self-hosting.

Will our data train models?

Not on enterprise API tiers that contractually exclude training. We will document and verify this for each chosen vendor.

What about hallucinations?

Mitigation via retrieval grounding, explicit "I do not know" behaviour, and human-in-the-loop checkpoints for high-stakes outputs.

How much should we budget?

Pilot work: typically €5–20k. Production AI workflows: monthly token cost varies; we model it per workflow.

Is on-prem AI realistic?

For specific cases yes — sensitive data, compliance reasons, or cost at scale. We will be honest about hardware reality (you need GPUs).

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