naas.ai

Leading the development of an open Universal Data & AI Platform to help organizations create powerful ecosystems of AI assistants

- Leveraging ontologies as a unifying field between data, AI models, workflows, analytics, and external systems
- Driving innovation in making data and AI accessible and affordable for organizations of all sizes
- Overseeing product development, business strategy, partnerships and team management

Founder & CEO

Forvis Mazars Group

Advising on projects from strategy to execution for Data & AI Products

- Focusing on creating profitable, auditable, and trustworthy AI solutions for clients
- Providing expert guidance on integrating data and AI technologies into business processes
- Assisting in developing strategies for AI adoption and implementation across various industries
- Collaborating with cross-functional teams to ensure successful delivery of data and AI initiatives

Senior Advisor, Data & AI Services

University at Buffalo

Conducting research on how executable ontologies can serve as a universal method for AI assistants/agents alignment, explainability, and compliance

- Exploring the intersection of philosophy, technology, and business in the context of AI systems
- Contributing to academic publications and presentations in the field of applied ontology and AI
- Collaborating with interdisciplinary teams to advance the understanding and application of ontologies in AI

Research Associate in Applied Ontology, Department of Philosophy

CashStory

Automation services company for business professionals.

- Developed a framework to help professionals approach data, automation & AI through Education and Open source products.
- Trained business professionals on how to take back control over their data and build an infinite solution maker mindset.
- Strived to build a better way to see financial & extra-financial information for wiser decision making, taking into consideration environmental issues & well being as much as cash, profit and value.

Founder

Technip

Technip, Paris, France (World leader in project management and engineering in the energy industry | Listed on NYSE EURONEXT CAC 40) 

Corporate Cash Manager, Group Treasury Department, April 2013 – Present  

Group Treasury Cash Management

• Perform daily treasury management and driving global liquidity initiatives
• Monitor Cash flows (by nature and by projects), Debt and Working Capital Requirement actuals and forecasts.
• Drive implementation of new structures to maximize cash available at HQ and minimize operational cash balances 
• Work with the treasury senior management on board/other executive presentations
• Develop sound relationships with banking partners for  Working Capital Management, Financial result optimization
• Act in constant relation with internal constituencies (Strategy, Group Consolidation, Tax, Legal, IT, Compliance)

Strategic Business Systems & Process Management 

• Project Manager/Administrator of the Group Treasury Systems (Diapason / Treasury Management Software, Hyperion / Business Intelligence tool) focusing on the continuous development of new functionalities. and implementation of the TMS
• Define cash management and Treasury system architecture of the future
• Lead cross organizational partnership for proposed treasury and finance strategy
• Develop clear project plans and ownership metrics (KPI’s) to drive accountability and execution throughout the group treasury organization.

Group Cash Manager

ESI Group

ESI Group, Paris, France (Pioneer and world-leading provider in Virtual Prototyping | Listed on NYSE EURONEXT Part C) 

Corporate Cash Controller, Financial Controlling, July 2011 – April 2013 

• Work closely with Board members (CEO, CFO, Director of Financial Operations) to integrate Cash in the financial monitoring of the group: development of Cash-flow reporting process, Balance Scorecard KPI's, bi-monthly cash flow anaysis consolidation, monthly usage during the Board. 

• In depth analysis of the financial impact of French R&D Tax Credit (Crédit d'impôt recherche), Taxes and Working Capital Management

• Build operating excel models at local and group level to challenge Cash forecast direct method

Cash Control Project Manager

Brittany Ferries

Onboard Sales

Schneider Electric

Schneider Electric, Chartres de Bretagne, France (Worldwide energy solution provider | Listed on NYSE EURONEXT Part A) 

Supply Chain Financial and Administrative Intern, Region EMEA and Asia Pacific, March 2009 – June 2009 

• Contact with clients/providers for credit collection (means and delay of payment) 

• Internal logistics control, order entry and invoicing and follow-up on orders in SAP  

• Relationship with logistics companies and shipping agents

Supply Chain Financial and Administrative intern

Comité National Olympique et Sportif Français

Membre du Club France aux Jeux Olympiques de Pékin 2008, Novotel Xin Qiao, Pékin, Chine
Au sein de l’équipe Réceptions/Bar: organisation events officiels & médias, soirées des médaillés, permanence journalière

Volontaire, Jeux Olympiques de Pékin 2008 (Beijing 2008)

Parker Hannifin

Mission in 2 subsidies : New Delhi, Inde (May 2008), Singapore (June 2008)
Objective : realize a qualitative study before the launch of a new product in Asia (focus on India)

Marketing Intern (May 2008 : New Delhi,Inde + June 2008 : Singapour)

⚡️ Building @naas.ai - open source data platform | Stanford LEAD alumni | Data strategy & mentoring

I'm Jeremy Ravenel. I’m a farm boy turned data mercenary and now an entrepreneur, I'm passionate about practical innovation to make our digital lives less chaotic.

I help people and companies create data & AI products that make their work easier and more efficient.

My journey started in finance about a decade ago. I thought I was entering an automated business world, but reality hit when I had to build reports using Excel and VBA. Spending more time producing than analyzing wasn't what I had in mind.

Out of frustration, I learned to code. I discovered Python and Jupyter notebooks, and suddenly, things that took hours were done in seconds. This led me to found CashStory, where we helped big French companies bridge the gap between business and tech teams.

Now, I'm working on something really challenging. At Naas.ai, we're building an open Universal Data & AI Platform. Our goal is to help any organization create their powerful ecosystem of AI assistants; leveraging ontologies as a unifying field between data, AI models, workflows, analytics, and external systems.

But that's not all. I'm also diving into research on Applied Ontology at the University at Buffalo, looking at how we can make AI systems more understandable and trustworthy. I'm also advising companies on Data and AI from strategy to execution with Forvis Mazars.

This mix of research, hands-on platform development, and strategy is something I’ve been dreaming about. I'm feeling very grateful for the opportunity to do what I'm passionate about at the intersection of philosophy, tech, and business.

I think anyone should be able to turn their data into a valuable asset. I try to build bridges to make it happen.

If you're curious about how data and AI can make your work easier and more impactful, let's connect!
Here is my email: jeremy@naas.ai

What if ontology can be better approached as a spectrum?

Over the past months I have seen, and contributed to ontology and knowledge graphs conversations. 

I’m glad the topic is gaining visibility, and that many organisations are beginning to understand why structured knowledge matters. Yet for most people, ontology still feels difficult to approach.

One reason is the idea that ontology only begins when you start writing formal logic or creating structured files. This creates a sense that ontology is something technical, abstract, or reserved for specialists.

Seeing it as a spectrum makes it easier to understand.

At one end, it starts with simple practices. Naming things clearly. Describing what exists in a consistent way. Making roles, actions and relationships explicit. These steps already bring clarity to how a team works and how it reasons about its environment.

At the other end, ontology becomes formal. Logical definitions. Coherent structures that can be validated, reused and eventually interpreted by AI systems. These models offer stability and precision, but they rely on the clarity built in the early steps.

The difficulty often comes from trying to jump directly to the formal end without recognising the value of the initial work. The discipline of describing reality clearly is what makes the rest possible.

Understanding ontology as a gradual process helps people engage with it from wherever they stand.

The discipline has been there for decades, but we are still early.

Jérémy Ravenel

My name is Jeremy Ravenel and I help people and companies create data products that optimize their time, money, and energy.⚡️

CashStory, the company I founded a few years ago, has been helping some of the biggest French companies (in the retail, luxury, or energy sector) bridge the gap between business and technical teams.

When I started working in Finance almost 10 years ago, I thought that I was entering an automated business world.

BUT during my first job, I was given the mission to build a reporting to give more visibility on cash to the top management. 

And I had to build it on Excel and VBA….

I was spending more time producing than analyzing.

And I quickly learned I was not alone.🔴

Out of my frustration, I had no choice but to learn the basics of coding.

I discovered the power of Python and Jupyter notebooks: the tools used by millions of data professionals in the world.

And I started selling my business and technical skills to companies.

We help our clients go from hours of reporting production to a few seconds.

But going from a need to a live data product was still very complicated for non-technical people.

This is why in November 2020, we open-sourced www.naas.ai : a data platform accessible to all.🟢

Naas enable data engineers, data scientists, business analysts, and all kinds of profiles, to create data products faster with templates. 

Since our soft launch, more than 2000 users from 65 different countries have subscribed to Naas

...and it’s awesome to see how they are using it for their personal and companies data projects.

People believe data science is expensive and difficult. Fortunately, that's not true anymore. 

There is a way, even if you don't have a technical bone in your body, you can transform your data into an asset. 

And my mission is to share this way with you.🌎

⚡️ Building bridges @naas.ai Universal Data & AI Platform | Research Associate in Applied Ontology | Senior Advisor Data & AI Services

What if the biggest shift in AI wasn’t about technology… but about how we deliver it?

At Forvis Mazars, we’re making the same organisational move that companies like Palantir, OpenAI, Mistral, Adobe, and Salesforce have taken:
bringing engineers forward, directly into the workflows of users, to map processes, model reality, and turn it into executable, auditable AI systems.

This is the foundation of the BOB program (built with NaasAI’s ABI framework) and the reason we’re opening Forward Deployed Software Engineer roles in 2026 (Internship)

These roles are designed for engineers who want to understand how organisations actually work, model those processes using ontologies, and turn them into executable logic through Python, semantic web technologies, and applied AI.

Not to build “features” or “models”,
but to understand how organisations operate, and encode that knowledge using:
- Ontologies (BFO, CCO, domain-level)
- Semantic knowledge graphs
- Python & process logic
- Trusted, explainable AI workflows

In practice, this means:
- Sitting with internal consultants, auditors, operators
- Mapping business processes from reality → ontologies
- Building AI systems that are transparent, sovereign, and auditable
- Deploying inside GAIA (FMZ) and contributing to the ABI open-source roadmap for external customers

There is a new delivery model for enterprise AI to be built, with analysts and engineers who can think in processes, model them, and operationalise them through ontologies and code.

Forvis Mazars is building the first practice in Europe that unifies:
- Ontology engineering
- Applied AI
- Process modelling
- Open-source infrastructure
- Real transformation at enterprise scale

If you want to learn the kind of engineering that will matter over the next decade, the one sitting at the intersection of business modelling, ontologies, and trustworthy AI, this internship is a unique entry point.

Feel free to reach out or apply directly, or ask questions below.

Link:
https://lnkd.in/exeGYsHY

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