Diagnosis
We analyse your marketing and sales workflows, tools and data. We identify repetitive tasks, decisions made without data and bottlenecks.
Deliverable: a map of your processes and of where time and value are being lost.
Bringing AI into your marketing strategy.
We do not sell software. AI only creates value once it enters your processes: how you produce, steer and decide. We work with leadership and marketing teams from idea to measured gain.
A method our founder applies first to his own marketing team, where AI agents are in production for performance analysis, content and reporting.
Our five-step method
Prioritisation
Each use case is scored on two axes: business impact and ease of delivery. We keep the two or three that pay back fastest and set the rest aside.
Deliverable: an impact and effort matrix and a 90-day roadmap.
Prototype
We build the first agents, automations or tools in days, connected to your existing stack and tested on your real data, with the teams involved.
Deliverable: working prototypes and a first measure of time saved.
Production
We write down your business rules and brand guidelines for the agents, put human review where it is needed and secure data access. Every use case has its own tracking metric.
Deliverable: processes that are tooled, documented and measured.
Team autonomy
We train your teams, build a library of reusable prompts and skills and set up steering rituals. The goal: your teams no longer need us.
Deliverable: trained teams and a setup that keeps improving.
Use cases
Performance management
Every week, an agent consolidates your media, CRM and sales data, analyses your campaigns creative by creative and delivers an annotated review: gaps, weak signals, proposed trade-offs.
Typical deliverable: a weekly performance review, ready for the leadership meeting.
Content production
Campaign variations, newsletters, product pages, video scripts, produced in your voice thanks to encoded brand rules.
Typical deliverable: a production pipeline with human review.
CRM and personalisation
Segments, lifecycle journeys and content tailored to each stage of the customer life cycle.
Typical deliverable: journeys ready to activate in your CRM tool.
Data in plain language
Your teams ask their questions in plain language and get sourced answers from your data.
Typical deliverable: an analysis assistant connected to your sources.
Visibility in AI engines (GEO)
Structured content, marked-up data and dedicated files to be picked up by ChatGPT, Claude, Perplexity and Google.
Typical deliverable: a GEO plan and optimised pages.
Web prototyping
Landing pages, internal tools and websites built in days to test an offer or a message.
Typical deliverable: a live page, measured and iterated.
Guardrails from day one
Human review
Nothing leaves the company without review. Agents propose, your teams decide.
Protected data
Minimal access, tools chosen to fit your security and compliance constraints, including GDPR.
Written rules
Your brand guidelines, vocabulary and business rules are written down and applied by the agents.
Measured impact
Every use case has its metric: time saved, quality, business effect.
Why a firm led by a CMO
An integrator knows the tools. A CMO knows what moves a P&L. Our founder led growth at Happn (from 3 to 42 million users) and ROI at Once Dating Group (from 64% to 142%); the firm ran EMEA performance marketing for Christian Dior Couture across 30 countries. We pick use cases through that lens: what pays back, first.
Five Anthropic Academy certificates earned by our founder (2026)
AI agents in production in Jolimoi’s marketing team
Twenty years in marketing, twelve in leadership roles
Our tools
We recommend the tool that fits your context, not the other way round. Our core stack:
- AI
- Claude (Anthropic), Claude Code, Claude Cowork, Agent Skills
- Prototyping
- Lovable
- Data and reporting
- Metabase, Looker Studio, GA4, Tableau
- CRM
- Klaviyo
- Integrations
- your existing tools (CRM, data warehouse, Slack, Notion, Google Workspace)
Three ways to work together
AI and growth diagnostic
A short, fixed-fee engagement: an assessment of your marketing, data and tools, followed by a 90-day roadmap of the AI use cases to launch first.
AI in production
We build the selected agents and automations with your teams, and stay until they are part of everyday work. Fixed fee or time and materials.
Fractional CMO
A few half-days a month alongside your leadership team: strategy, budget, organisation, with AI built into how the marketing team runs.
Frequently asked questions about AI
Where should you start when bringing AI into marketing?
With a diagnosis: map the repetitive tasks and the decisions that lack data, then pick two or three high-impact use cases. Starting with the tools gets the problem backwards.
Do you need a technical team to get started?
No. The agents and automations we set up build on your existing tools. A data or tech team speeds things up, but it is not a prerequisite.
How long before you see results?
The first time savings show up at the prototype stage. Business impact is measured once the new ways of working are embedded in your processes.
Which AI tools do you use?
Mainly Anthropic’s Claude ecosystem, in which our founder is certified, complemented by prototyping tools such as Lovable and by your business tools. We recommend the tool that fits your context.
How do you protect our data?
Minimal access, tools chosen to fit your security and compliance constraints, human review of any published content. This framework is set before the first prototype.
Do you train teams?
Yes. Upskilling is part of every engagement: hands-on sessions, reusable prompts and skills, documentation.
Let’s talk about your growth.
A first 30-minute conversation to understand your situation and see how we can help.