We help companies identify and deploy the AI use cases that create value for their business. Marketing and data first, our field of expertise since 2018.
Identifying and deploying the AI platform, connecting your business context and your data, building the agents and the workflows. With the governance, the security and the training your teams need to use them.
EdgeAngel is a data marketing and AI agency, and an independent consultancy. We work with marketing, data and IT teams, from data foundations to agents in production, so that your AI projects turn into productivity gains and business value.
Our approach
We support our clients across the whole chain of an AI project, or on part of it, depending on how far along they are. We favour implementing the governed platforms of the market (Claude Team and Enterprise, Gemini Enterprise, ChatGPT Business and Enterprise, Mistral AI) and building agentic assets shared across your organisation.
The first decision is not the model, it is the framework. Who has access to what, for what purpose, under which rules.
We build what you need, identified together with your teams. Versioned files in your own repository, portable from one platform to another.
A few examples of what we have built: SEO and GEO briefs produced from a semantic audit, campaign reports written on consolidated data, incrementality analyses, data collection alerts, ad variant ideation and production.
We have tested that portability for real: we migrated the whole team from one agentic environment to another in less than a day, without rewriting a single asset.
This is the key. A model works well when it is connected to the right data and to the right business context.
An agent that does not evolve goes stale. Models change, and so do your rules.
We practise what we install. Our consultants work every day with the same assets as those we deploy at your end.
A concrete case
A use case in production, step by step. The approach is the same on other subjects, and the first stage does not mention AI yet.
01
Media, analytics, CRM and back-office data flow daily into the warehouse, through an ETL: yours if you have one, or ours, Capture. Sync, normalisation, history. Comparable data across every channel.
02
On top of the warehouse, a semantic layer defines every metric and records the quirks of each source. A real example: detecting the country by pattern in the campaign name, with a fallback rule when the pattern is missing. That level of detail is what separates a correct figure from a wrong one.
03
The analysis method becomes a plugin: a set of skills carrying your rules, sub-agents that split the work, code executed when a calculation needs it, and MCP connectors to your data. Readable by a human, installed on your teams' workstations.
04
With the agent, the consultant understands and analyses performance far faster, and turns it into clear, readable reporting. They also feed back new angles of analysis and the adjustments to make: the agentic workflow keeps improving.
How we work with you
We offer both, and they often combine. What changes is the engagement format and where the project starts from.
We mostly work at the end of the AI chain, the part closest to business use cases: the part that turns a project into a productivity gain or into business value. Every workflow we build becomes an asset we bring to our clients, maintain and keep improving.
We also work on infrastructure when the project calls for it: cloud, custom AI deployment, RAG (retrieval augmented generation) over your document bases, model fine-tuning. On those specific projects we bring in partners such as Silex or other experts from our network, and we stay in charge of the engagement.
Secondment
A consultant embedded in your team and your rituals, for a defined period. We draw on our own people and on our partner network, agencies and independents.
Our method
We start from a first use case with clear value, we make the data it needs reliable, and we extend from there.
More about the agencyAudit of usage and available data. We identify the tasks where AI saves measurable time, prioritise them, and inform the platform choice.
Consolidating and documenting the data the first agent needs. Access, secrets, logging, compliance.
Skills, MCP connectors, private marketplace. A first agent in production, used by a real team on real work.
Training, steering committee, continuous updates. What usage reveals feeds back into the agent, iteration by iteration.
We work on framing alone, on the full build, alongside your AI team, or by placing a consultant with you.
Our publications
Testimonials
With the Capture solution for our reporting and the quality of consultants, our performance reviews have become ultra-clear and relevant. This allows us to manage daily activities and gives us the means to achieve our goals.
Mathias Pestre-Mazieres CEO Blue Horse Group
An acquisition strategy that perfectly secured our high season. Thanks to fine-tuned management of the Google / Meta complementarity, we were able to scale our volumes with controlled profitability.
Lydie Castagnet Marketing & Communication Director Forge Adour
EdgeAngel is not limited to media buying, they give meaning to numbers. They were able to detect weak signals in our data to transform our acquisition and unlock new performance levers.
Valentine Soulès E-commerce Manager Golf One 64
Since the deployment of Capture by EdgeAngel, our SEO team has significantly improved reporting quality and opportunity analysis: the reports are highly performant, with very advanced granularity (+30 million rows in the dataset) and complete team adoption.
Karim Elmlih Head of Organic Acquisition – Growth Qonto
Partners since 2018 on our tracking and privacy challenges (Piano, sGTM, GDPR), EdgeAngel combines sharp technical expertise with rigor. An essential extension of our team to secure and accelerate our complex data projects.
CĂ©dric Tamboise Group Digital & e-Commerce Director Kiloutou
Since 2021, EdgeAngel has been securing our Web & App tracking. Their advanced technical expertise has enabled us to regain full control of our data to effectively drive the evolution of our digital ecosystems.
François Charlet Communication and Digital Marketing Citeo
Our solution
Connect your tools to each other and feed your AI and agentic workflows with your data and your business context. Capture augments your existing infrastructure and makes it more efficient: you remain the owner of the tools and the data.
The agency
Hubs in Paris, Bordeaux and Barcelona. You know who works on your account, and you talk directly to the consultants who run it.
FAQ
An AI agency helps a company move from individual use of artificial intelligence to a setup its teams use every day. The scope varies a lot from one player to another: that is the first question to ask.
Ours covers four stages:
Our core is the end of the chain: business use cases and getting them into production. We also work on infrastructure when the project calls for it, from cloud to RAG and fine-tuning, bringing in partners such as Silex or other experts from our network. And we offer a secondment model, with our own consultants or our network.
Agentic AI is when a model chains actions to complete a task, rather than answering a question: fetching data, applying a calculation rule, producing a document, flagging an anomaly.
What changes in practice is how demanding it becomes about context. A conversational answer tolerates approximation. A chain of actions does not: one wrong definition at the third step makes everything after it wrong, without anyone noticing.
That is why we document the data first, then build the agent on top of it.
Yes. Connecting an agent to the right data and to the right business context is the condition for models to work well.
An agent connected to raw tables answers quickly, and off the mark. What makes it reliable is the documentation it reads: definitions written by people who know the subject, and the business rules that go with them.
In practice we first make reliable what the first use case needs, rather than waiting for all of the company's data to be perfect.
The choice follows your existing ecosystem, not a model leaderboard that changes every six months. Google suite, Gemini Enterprise. Microsoft suite, Copilot. With no strong preference, Claude and ChatGPT are a few months apart.
If European hosting or data sovereignty weighs on the decision, Mistral AI enters the comparison, with its enterprise offering and models deployable on your own infrastructure.
The non-negotiable point is the enterprise plan, Team or Enterprise depending on your size: it carries the organisation rules, retention and logging.
We resell no licence, so we have no interest in you buying one rather than another. What matters more: designing your assets to be portable. Skills in plain text and connectors on the Model Context Protocol standard travel. A configuration locked inside a vendor's interface does not.
A few weeks on a framed scope, a few months for a setup installed across several teams. The heaviest factor is not building the agent: it is the state of the data it has to read and how long access takes to obtain.
We frame in two steps: a conversation to qualify the use case and the state of the data, then a proposal with a scope, a timeline and a budget.
You do, and it is verifiable on three counts:
If you change model, platform or partner, the setup follows. It is a deliberate choice, and it makes us replaceable. We would rather be kept for the value we create.
Yes, that is one of our formats. We place a consultant with you or alongside your partner, for a defined period. We draw on our own people and on our partner network, agencies and independents.
The profiles most often asked for: AI Engineer, Machine Learning Engineer, LLMOps Engineer, AI Architect, Agent Developer, Data Scientist. And if the skill becomes critical for you in the long run, we will tell you that hiring is the right move.
Yes, and that is why we know what holds up. The whole team works with assets we built ourselves: account audits, campaign reports on consolidated data, editorial briefs, data collection quality checks.
The setup is the same as the one we install for our clients: skills versioned in a repository, MCP connectors to our warehouses, a private marketplace deployed on every workstation. What we deploy at your end has served at ours first.
Get in touch
A first call to understand your context, and tell you what is feasible and under which conditions.
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Or call us directly: +33 1 84 16 42 20
Paul Schmitt
Consulting Director
"Our goal is to make your data actionable to generate concrete value, quickly."
The team