LLM advisory: AI strategy and governance
Select, evaluate and govern large language model use cases.
When to bring us in
Document analysis, drafting and knowledge assistants can be useful only when teams understand permitted data, quality standards and the consequences of errors. Start with a bounded pilot and evidence-based evaluation.
What the engagement delivers
Use-case map; model selection criteria; evaluation protocol; prompt library; human review rules; deployment roadmap.
Prepare for our first conversation
List tasks, volumes, existing tools, sensitive data and unacceptable failures. Involve IT, security, legal and privacy teams in technical decisions.
An agreed scope of work
We agree on objectives, audiences, markets, deliverables, responsibilities, timing and availability. The proposal separates advisory work, content production and any third-party services. Media coverage, search rankings and regulatory outcomes cannot be guaranteed.
How an engagement works
- Frame the decision: focused interviews, available evidence, constraints and criteria for success.
- Develop the response: diagnosis, reasoned options, messages and materials reviewed by the designated owners.
- Prepare delivery: a timetable, clear responsibilities, spokesperson preparation and response scenarios.
- Review and adapt: assess activity, unresolved questions, lessons and the next decisions.
Scope your LLM use cases
A short introduction is enough to start: your organisation, the decision at hand, the audiences involved and your deadline. Confidential documents can follow through an agreed channel.
Email Belief SystemFrom insight to action
Technology, AI and cybersecurity
Technology earns credibility when people understand what it can do, what it cannot do and who is accountable.
Finance, banking and insurance
Trust in financial services depends on consistency between governance, decisions and public explanations.
Reputation dashboard: template and indicators
A reputation dashboard should inform decisions.