Generative AI Consulting
Find the generative AI use cases worth pursuing and the fastest safe path to value. We cover model selection, RAG architecture, evaluation and EU AI Act conformity, grounded in production experience.
What generative AI consulting covers
Generative AI moves fast and most of the risk sits in the details: the wrong model, no evaluation, or a design that cannot be governed. Consulting is about avoiding those traps before you commit budget.
We help you pick the right use cases, choose between models, design retrieval and guardrails, and put an evaluation harness in place so quality is measured rather than assumed.
- Model selection across hosted and open-weight options.
- RAG and guardrail design that survives real inputs.
- Evaluation and EU AI Act conformity built in from day one.
Generative AI strategy
A generative AI strategy answers one practical question: which three use cases should you start with. We collect ideas from your teams, then score each one on business value, data readiness, risk and effort. The best first projects have a clear owner, enough data, a measurable outcome and a low cost of mistakes.
Typical strong candidates are drafting and summarising documents, answering internal questions from company knowledge, and extracting data from incoming emails and files. Use cases that make decisions about people or money usually come later, once the foundations are in place.
Choosing the right model
There is no single best model. We compare candidates on your own data and tasks, looking at quality, latency, cost and data protection.
- Commercial models: strong out of the box and quick to start, available through EU-hosted endpoints from several providers.
- Open models: such as Llama or Mistral, which you can host in your own cloud for full control over data.
- Smaller models: often good enough for classification and extraction, and much cheaper at volume.
We design the architecture so you can switch models later without rebuilding the application.
Build your generative AI roadmap
The roadmap turns the strategy into a plan your team can execute. It covers the first use cases with owners and success metrics, the data and integrations each one needs, the governance and EU AI Act checks, the skills to build in-house, and a 90-day plan for the first pilot.
Most clients start with a short assessment and a workshop. The roadmap that comes out of it is specific enough to start building the next week.
Where we help
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Use-case selection
We separate the demos from the durable wins and sequence the ones with a clear owner, clear data and a measurable outcome.
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Architecture and model choice
RAG design, prompt and context strategy, and model selection tuned to your accuracy, latency and cost constraints.
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Evaluation and governance
An evaluation harness against real inputs, plus the documentation and controls the EU AI Act expects.
Frequently asked questions
What does a generative AI consultant do?
Helps you pick use cases where generative AI pays off, chooses models and architecture, estimates cost and risk and plans the rollout.
Should we use an open-source or a commercial model?
It depends on data sensitivity, cost and quality needs. We test both on your data before recommending one.
How do we keep generative AI costs under control?
With caching, smaller models for simple tasks, usage limits and a cost-per-task metric tracked from day one.
Put generative AI to work, safely
Tell us what you want generative AI to do. We will map the use cases and the fastest safe path to production.