Thought leadership & AI discoverability for expert-led organizations
How I can help.
The question is no longer whether you are publishing enough. Volume, we have learned, is a metric for a different game. Visibility, now, is citability. You want to get found and cited in AI Overviews, Claude, ChatGPT, Perplexity, and others. And when you’re not in the room, AI should have something true to say.
What travels and compounds with readers and generative search engines alike, is original work, rigorous and coherent across multiple channels and formats. But expertise rarely speaks for itself. Deep knowledge is challenging to share, and harder still to get accurately represented.
I turn expertise into source material: a body of thought leadership and reliable working methods that make what your organisation knows understood and citable, by people and by the AI systems now answering in your place.
I start from what you know, whatever the form: proprietary data, methodologies or frameworks, and the ideas already living in your organisation. From there, I build what carries it forward: clear message architecture, pillar pieces, and a cohesive editorial and visual system. All of it structured to increase the probability of accurate retrieval and attribution in AI search. The thinking, and the voice, stay yours.
Built to evolve as AI and discovery change.
For organisations whose value is expertise. Exavoice helps turn knowledge into source material that builds authority with audiences and earns visibility inside AI search. Compelling and designed to be accurately represented in text and images, and on AI surfaces.
Thought Leadership & Authority
Not more content for the sake of it, but a stronger information footprint.
Research-driven and interview-based pieces that turn proprietary expertise into clear, evidence-rich material for audiences, prospects, and AI-mediated discovery.
Typical work includes:
Pillar briefs: input from subject-matter experts, evidence, narrative direction, and positioning in relation to competitors or the wider conversation
Organisational thought leadership: flagship articles, research reports, and data-led narratives
Executive thought leadership: publication-ready pieces built around an executive’s ideas
Evidence, attribution, and retrieval design: clear claims, credible sources, expert credentials, and structures that make important material easier to verify, find, parse and interpret
Supporting execution may include proposal and pitch narratives, and visual-verbal alignment.
Available in French, English and Spanish, enabling seamless collaboration with international teams.
Content systems & AI search readiness
Your expertise, easier to express, extend, and discover by readers and AI search.
Content systems that create a more durable body of expert material, carry it consistently across formats, and give you a repeatable view of how your organisation is found and represented in AI-assisted discovery.
This includes:
Content audit and mining: what you already have, what is missing or can be reused
Message architecture: what you stand for, proof points, narrative themes
Editorial planning, aligned with your business cycles, from conferences to launches
Format and channel adaptation: turning one strong idea into assets for LinkedIn, newsletters, website, PR, speaking, and audio or video scripts
AI discoverability (AEO|GEO): looking beyond your own content to map the external sources and mentions that also shape visibility
Representation and visibility tracking: a baseline of how AI systems describe you or your ideas, remeasured on a schedule
Hybrid workflows & AI guardrails advisory
For experts and teams who want a more deliberate way to use AI across research, writing and visual work, without losing judgement and control. And where it absolutely doesn’t fit.
What we do together:
Map your current workflow and AI stack: where time leaks or quality drops, and where tools complement each other, add value or complexity
Set up a research process that is more reliable, from sourcing and fact-checking to synthesis
Put guardrails in place: identify where language and image-generation models introduce risk and build relevant EU transparency requirements into editorial practice
Add lightweight visual asset support tied to your editorial system
Working with uncertainty
AI systems are non-deterministic: what they retrieve, whom they cite, and how they frame an answer varies by engine, by query, within the same day, and their selection criteria are largely opaque.
That's why this work doesn't chase tricks or promise placements. It strengthens the factors that tend to improve representation across systems: original material, clear provenance, verifiable expertise, coherent structure. The inputs are yours to control. I make them as strong as they can be. And we track changes.