In a context where artificial intelligence is redefining traditional business models, choosing an AI agency in Paris becomes crucial for successfully achieving your digital transformation. Specialized companies like Daijobu AI now offer a structured client journey, from identifying needs to implementing personalized solutions. Let’s explore together the different phases of this collaboration and how Daijobu AI, a Parisian AI agency, can transform your organization by boosting its efficiency and innovation capacity.

The Importance of a Well-Defined Client Journey in AI

The success of an artificial intelligence project doesn’t rely solely on the technical quality of the developed models, but also on the methodology employed throughout the project. AI agencies like Daijobu AI structure their approach around a clearly defined client journey, thus maximizing the chances of success for each initiative.

According to recent McKinsey studies, companies that have fully adopted AI state that it contributes to creating a better customer experience for 86% of them. However, as revealed by the Bpifrance Le Lab survey, only 3% of VSE/SME managers make regular use of AI and 12% make occasional use, often due to lack of vision on the path to follow.

Structured support from your AI provider ensures that the developed solutions precisely meet the specific needs of the company, integrate harmoniously into its existing systems, and generate measurable impact on its performance.

Key Stages of the Client Journey with Daijobu AI

Stage 1: AI Diagnosis – Exploring Your Data’s Potential

The first stage of the client journey with Daijobu AI consists of an in-depth diagnosis of AI opportunities within your organization. This crucial phase allows identification of high-impact use cases by analyzing your data and transformation objectives.

As recommended by Business Decision in its methodological guide, this phase begins with acculturation of management and operational teams. Our AI lab experts start by understanding your business challenges and exploring your data ecosystem. This approach allows mapping concrete opportunities and identifying “quick wins” – those projects with high potential and relatively simple implementation that will quickly demonstrate AI’s value for your company.

At the end of this stage, you’ll have a clear roadmap, prioritizing use cases according to their potential impact, technical feasibility, and alignment with your strategic objectives.

Stage 2: Development of Your Personalized AI Solution

Once the priority use case is identified, our AI Lab moves to the development phase. This stage includes the design and training of a personalized AI model, using your own data to guarantee maximum relevance.

According to an IBM study, 45% of companies exploring or already deploying AI declare having accelerated their deployment or investments in this technology, highlighting the importance of this development phase.

This phase is characterized by:

Model architecture: creation of an architecture adapted to your specific use case Data preparation: cleaning, structuring and enriching your data to optimize training Model training: using your data to create a custom model, exclusively dedicated to your use Testing and validation: rigorous evaluation of model performance to guarantee its reliability

The iterative approach adopted by the best AI agencies in Paris allows progressive refinement of the model, in close collaboration with your teams, to ensure it perfectly meets your requirements. This methodology draws inspiration from best practices recommended by sector experts, who favor progressive deployments and constant adjustments.

Stage 3: Deployment and Iteration – Bringing Your Solution to Life

The third stage marks the launch of your AI solution via a secure API and dedicated platform. Daijobu AI supports this deployment with integration support and continuous performance optimization.

According to an analysis by France Num, this phase is often considered critical by VSEs/SMEs who perceive the difficulty of integrating these technologies into their existing processes. This is why support from an AI agency is particularly valued.

This phase includes:

Technical integration: setting up necessary connections with your existing systems Training your teams: skills transfer to enable you to effectively use the solution Performance monitoring: tracking key indicators to measure the solution’s real impact Continuous improvement: regular iterations to improve the model based on usage feedback

According to Blog du Modérateur, 73% of French people declare not feeling sufficiently trained to effectively use AI tools, hence the crucial importance of training and support during this phase.

Stage 4: Total Control and Transparency – “Full Control, Always”

The last stage of the client journey, often neglected but essential, concerns the long-term governance of your AI solution. Only certain providers, like Daijobu AI, truly guarantee total transparency on the use of your data and provide you with the necessary tools to maintain control.

This approach aligns with CNIL recommendations which emphasize the importance of data control and transparency in AI projects to ensure GDPR compliance.

This “Full control, always” philosophy translates to:

Total data control: complete mastery of data used for training and generated by the model Sovereign hosting: secure infrastructure in France, guaranteeing compliance and security Innovative leasing system: you become owner of your solution, transforming an operational cost into a sustainable investment

As explained in the Unite.AI report on data sovereignty, “AI-based frameworks allow organizations and individuals to directly manage who can access their data and how it is used,” which constitutes a major strategic issue in the AI era, particularly for Parisian AI agencies that emphasize digital sovereignty.

An Economic Model Adapted to Your Needs

Daijobu AI is the only AI agency in Paris to offer a flexible economic model, allowing optimization and amortization of your expenses:

• An initial payment covering the startup costs of your AI project
• Fixed monthly fees and usage-based costs, adapted to your actual use
• A purchase option allowing buyback of the model at contract end, with choice of hosting

This leasing approach allows significant reduction of initial investment while offering you the possibility to become owner of your AI solution, which is particularly interesting in a context where 65% of French executives and managers consider digital sovereignty as a major issue for their company.

Advantages of Partnership with an AI Agency in Paris

Local Expertise and Global Vision

An AI agency combines deep understanding of the local economic fabric with a global vision of the latest technological advances. This dual expertise allows designing solutions perfectly adapted to your market’s specificities while drawing inspiration from international best practices.

As highlighted by OCI in its analysis on digital sovereignty, this local approach is decisive for “mastering one’s future and securing growth” in the AI context.

Sovereignty and Regulatory Compliance

By choosing Daijobu AI, you benefit from an approach respectful of European regulations regarding data protection (GDPR). Sovereign hosting in France of your models guarantees security and confidentiality of your sensitive data.

Proximity Support

Geographic proximity with an AI agency in Paris facilitates regular exchanges and collaborative workshops, essential for the success of complex AI projects. This human dimension of partnership strengthens communication quality and accelerates resolution of potential problems.

Conclusion: Choosing Excellence with an AI Agency in Paris

The client journey offered by an AI agency in Paris like Daijobu AI represents much more than a simple technical service. It’s a true strategic partnership, designed to support you at each stage of your transformation through artificial intelligence.

According to McKinsey forecasts cited by LearnThings, AI could create 2.3 million new jobs by 2025, and 70% of leaders estimate that AI will contribute to creating new roles and careers. To benefit from this revolution, choosing an expert Parisian AI agency is decisive.

By choosing Daijobu AI which places control, transparency and personalization at the heart of its approach, you ensure not only benefiting from high-performance AI solutions, but also gradually acquiring the autonomy necessary to fully master this strategic technology.

The difference between simple technical implementation and successful transformation often lies in the quality of this client journey, from initial exploration of opportunities to deployment of a solution perfectly adapted to your specific needs.

The difference between simple technical implementation and successful transformation often lies in the quality of this client journey, from initial exploration of opportunities to deployment of a solution perfectly adapted to your specific needs.

Millions of tokens now constitute a fundamental metric in the world of artificial intelligence models. This unit of measurement, though often invisible to end users, determines the efficiency, performance, and cost of AI systems.

Whether you’re a business leader evaluating AI solution integration, a developer working on language models, or simply passionate about technological innovations, understanding the million tokens for AI model metric is now essential.

This article offers an in-depth exploration of the world of tokens: their nature, how they’re calculated, and their decisive impact on the strategic deployment of AI projects.

What is a token in AI?

A token constitutes the fundamental processing unit for language models. Contrary to popular belief, a token doesn’t exactly correspond to a word or character, but rather to a fragment of text that the AI model interprets as an indivisible entity.

In the French language, a token can represent:

• A short word in its entirety (“le”, “une”, “donc”)
• A portion of a more complex term (“intellect” becomes “intel” + “lect”)
• A punctuation mark (“?”, “!”, “.”)
• A space separating two words

Linguistic studies applied to AI estimate that on average, a token is approximately equivalent to 0.75 words in French or English. Therefore, a standard page containing 500 words generally requires between 650 and 700 tokens to be fully processed.

See how this work with OpenAI’s online tokenizer !

Why measure in millions of tokens?

The adoption of the scale of millions (or even billions) of tokens as a reference in the industry is explained by several determining factors:

The scale of training data

Contemporary AI models rely on textual corpora of staggering size. For example, modern models are trained on datasets representing several hundreds of billions of tokens. This monumental scale necessitates the use of a measurement unit adapted to these massive volumes.

Contextual analysis capacity

A model’s context window—the amount of information it can analyze simultaneously—is also measured in tokens. The most sophisticated systems can now process up to one million tokens in a single query! This capability radically transforms the depth of analysis and the relevance of generated responses.

Economic structuring of the sector

The majority of AI service providers have adopted pricing proportional to the number of tokens processed, generally billed in increments of one million. This economic model, which has become standard, profoundly influences the design and optimization of AI-based applications.

Impact on costs and performance

The economic dimension of tokens

The token-based pricing system has established itself as the reference economic model in the generative AI ecosystem. As an indication, current price ranges generally break down as follows:

• Accessible models: €0.50 to €2 per million tokens
• Intermediate models: €2 to €10 per million tokens
• High-end models: €10 to €30 per million tokens

For an organization regularly processing large volumes of textual data, these costs accumulate quickly. An enterprise conversational system can easily consume several tens of millions of tokens monthly, transforming this technical metric into a major budgetary issue.

The determining influence on result quality

The number of tokens directly impacts the quality of results produced by an AI system:

Depth of contextual analysis

The more tokens a model can process simultaneously, the more its ability to maintain coherence over long texts improves. This characteristic proves particularly crucial for analyzing legal, medical, or technical documents.

Richness of instructions

Detailed instructions, requiring more tokens, generally produce more precise results better aligned with the specific expectations of the user.

Conversational continuity

In dialogue applications, preserving the complete history of exchanges requires a significant volume of tokens but significantly improves the relevance and fluidity of generated responses.

The risk of exploding bills: understanding the cumulative effect of tokens

An often underestimated aspect of using AI models concerns the cumulative effect of tokens on cost structure. This phenomenon can transform an initially profitable project into a real financial sinkhole.

The snowball effect of contexts

In conversational applications like enterprise virtual assistants, each interaction with the user enriches the global context. Take a concrete example: after just ten exchanges, a standard virtual assistant can accumulate several thousand tokens solely to maintain the contextual coherence of the conversation. If this accumulation is multiplied by hundreds of daily users, the system quickly generates tens of millions of additional tokens each month.

A striking illustration: a financial services company using a virtual assistant for customer relations saw its monthly bill increase from €2,000 to over €15,000 within a quarter. The cause? Their system kept the entirety of conversation histories without any optimization strategy or memory management.

The sophisticated pitfalls of advanced models

The most sophisticated models, despite their superior performance, also present higher financial risks:

The temptation of contextual exhaustiveness

With models supporting extended contexts up to 1,000,000 tokens, the temptation becomes strong to include entire documents as contextual reference. However, at an average rate of €20 per million tokens, each fifty-page document added to the context can represent an additional cost of one euro or more per query.

The spiral of iterative interactions

Complex projects frequently require multiple exchange cycles with the model. Each iteration multiplies the costs, particularly when the context becomes voluminous. A simple strategic analysis can thus require dozens of back-and-forths, each integrating an increasingly enriched context.

Optimization and alternatives to token-based billing

Faced with these economic challenges, optimization becomes a strategic issue to ensure the financial viability of AI projects. The most effective approaches combine several complementary dimensions:

The art of contextual conciseness

Writing precise but concise instructions, as well as selective management of conversational history, can considerably reduce the token footprint. This writing discipline, far from trivial, often requires specific expertise to maintain the balance between token economy and informational richness.

The excellence of algorithmic customization

Fine adaptation of models specifically calibrated to respond to particular use cases not only improves the relevance of generated responses but also drastically reduces the volume of tokens needed. Daijobu AI has specifically specialized in this approach, developing customized models that generally require between 60% and 80% fewer tokens to achieve equivalent or superior performance compared to generic solutions.

Prompt-based billing: the alternative proposed by Daijobu AI

Faced with the inherent unpredictability of token-related costs, Daijobu AI has developed an alternative billing approach, centered on the prompt rather than the million tokens (MToken). This pricing innovation presents several strategic advantages for organizations:

Budgetary predictability as a foundation

By billing for usage (per prompt or per query) rather than token volume, companies can anticipate their costs with remarkable precision. A customer service handling 10,000 monthly requests knows its budget envelope precisely, regardless of variations in exchange complexity.

Alignment with business value creation

Each query typically represents an interaction generating value for the organization (a resolved customer question, an analyzed document, etc.). Prompt-based billing thus establishes a direct correlation between incurred costs and produced value.

Structural incentive for technical excellence

This pricing model naturally encourages Daijobu AI to continuously perfect its own models to optimize their token consumption, thus creating a virtuous and collaborative dynamic with its clients.

In its concrete application, this innovative pricing model generates substantial savings. A Daijobu AI client company, using a solution in automated document processing, reduced its AI costs by 76% by migrating from a conventional solution billed by MToken to a customized system billed by prompt.

For data-intensive uses (autonomous agents, analysis of vast document corpora, or generation of complex reports), Daijobu AI also offers hybrid formulas, combining a fixed cost per prompt with token consumption ceilings, thus offering an optimal balance between budgetary predictability and operational flexibility.

Conclusion

An in-depth understanding of the unit of measurement in millions of tokens now asserts itself as a strategic prerequisite for any organization integrating artificial intelligence into its processes. This metric, far from being purely technical, profoundly influences not only the cost structure but also the quality and operational efficiency of deployed AI solutions.

The potentially exponential increase in bills linked to the progressive accumulation of contexts constitutes a very real financial risk that organizations must imperatively anticipate. Faced with this challenge, the innovative approach developed by Daijobu AI—combining customized, highly efficient models and prompt-based billing—offers a particularly relevant alternative that transforms budgetary unpredictability into financial stability.

For decision-makers seeking to maximize the return on investment of their AI initiatives, a strategic approach to token management, potentially associated with a redefinition of the billing paradigm, can constitute the fundamental difference between a costly project with uncertain results and a high-performing solution generating substantial, measurable, and predictable added value.

Would your organization like to optimize its token consumption or explore more predictable billing alternatives for its AI projects? Daijobu AI’s experts are at your disposal to conduct a personalized audit of your specific needs.

FAQ on millions of tokens

What is the difference between input tokens and output tokens?

Input tokens correspond to the text transmitted to the model (queries, instructions, context), while output tokens are those generated by the model (responses, content). In most pricing structures, output tokens are billed at a higher rate, reflecting their higher computational cost.

How can I precisely estimate the number of tokens in a text?

Many online analysis tools allow for precise estimation of a text’s token volume. As a first approximation, you can divide the number of words by 0.75 to obtain a rough estimate of the corresponding number of tokens.

Are tokens counted identically in all languages?

No, Asian languages like Mandarin or Japanese generally require more tokens per expressed concept than Indo-European languages. This linguistic difference can have important budgetary implications for multilingual applications.

What does one million tokens concretely represent in textual volume?

One million tokens is approximately equivalent to 1,500 standard pages (at 500 words per page), or the equivalent of about four to five medium-sized novels.

Does fine-tuning a model effectively reduce token consumption?

Absolutely. A model refined for a specific domain or use can generally produce higher quality results with a more restricted context, thus significantly reducing the volume of tokens required for each interaction.

Recent OECD findings reveal that while AI adoption among SMEs is growing, most businesses aren’t maximizing its potential. Discover how custom AI solutions can help your business overcome the most common barriers to digital transformation.

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Artificial intelligence is rapidly transforming the French business landscape. For Parisian companies looking to stay competitive, choosing a specialized AI agency has become crucial. This guide supports you in this strategic approach to identify the ideal partner for your digital transformation.

Why Partner with an AI Agency in Paris?

Paris Tech Ecosystem in Full Expansion

Paris has established itself as a major European tech hub, concentrating innovative startups, incubators, and AI talent. This local dynamic offers companies privileged access to cutting-edge expertise and tailor-made solutions.

The Île-de-France region hosts more than 40% of French tech companies, creating a fertile ecosystem for AI innovation. This concentration of expertise fosters exchanges, collaboration, and the emergence of innovative solutions adapted to contemporary business challenges.

Benefits of a Local Partner

Choosing an AI agency in Paris offers concrete benefits. Geographic proximity facilitates regular exchanges and project management, essential elements for complex innovation projects. A local partner has perfect mastery of the French regulatory context, particularly GDPR requirements and sector-specific regulations.

Hosting on French infrastructure guarantees data sovereignty, now a priority criterion for many companies concerned with protecting their strategic assets.

Overview of Parisian AI Agencies

Strategic Consulting Specialists

These AI agencies focus on decision-making support, helping executives define their AI strategy and identify the most relevant transformation opportunities. They excel in data auditing and prioritizing use cases according to their business impact.

Technical Solution Developers

True technological architects, these AI agencies create personalized AI models and develop business applications integrating artificial intelligence. Their expertise covers the entire technical spectrum, from generative AI to predictive neural networks.

Full-Service Partners

Full-service AI agencies, like our approach at Daijobu AI, offer end-to-end support. This comprehensive approach ensures optimal consistency between strategy, development, and deployment, while simplifying project management on the client side.

AI Agency Selection Criteria

Technical Expertise and Sector Experience

The ideal AI agency masters the three pillars of modern AI: content generation to create creative solutions, predictive analysis to anticipate trends, and operational automation to optimize business processes.

Prioritize an AI agency that has already supported companies in your sector. This sector experience guarantees a refined understanding of your specific challenges and significantly accelerates the design phase.

Methodology and Project Approach

A serious agency systematically offers an initial diagnosis to identify priority use cases and evaluate your data maturity. This audit phase conditions the success of the entire project.

The iterative approach with rapid prototype development allows validation of hypotheses and solution adjustment before full investment. This agile methodology significantly reduces project risks.

Security and Data Sovereignty

Security constitutes a non-negotiable prerequisite. Require hosting on sovereign French infrastructure, ideally ISO 27001 certified and scrupulously respecting GDPR.

Total control of your training and production data must be guaranteed contractually. An ethical AI agency formally commits to never using your data to train other models or share it with third parties.

Economic Transparency and Financing Models

Look for an AI agency in Paris offering flexible economic models adapted to your financial structure. AI leasing solutions allow investment spreading while maintaining final intellectual property of your solution.

Pricing transparency avoids unpleasant surprises. A detailed quote must clearly distinguish development, hosting, maintenance, and usage costs.

Essential Questions for Your Selection

Expertise Validation

Request concrete demonstrations of projects similar to yours, with measurable performance metrics. An experienced agency willingly shares its feedback and results obtained for its clients.

Question them about their technological watch and adaptation capacity to rapid AI sector evolutions. Technologies evolve quickly; your partner must anticipate these changes.

Support and Training

Adoption by your teams conditions your AI project’s success. Verify that the agency offers change management support and training adapted to different user profiles.

Post-deployment technical support quality determines your investment’s sustainability. Clarify maintenance and solution evolution modalities.

Common Mistakes to Avoid

Prioritizing Price Over Value

An attractive rate sometimes hides limited services or hidden costs. Prioritize long-term value creation over immediate savings. A poorly designed solution generates exponential correction and maintenance costs.

Neglecting Data Quality

The most sophisticated AI cannot compensate for poor data quality. Ensure the agency seriously evaluates your data heritage and proposes cleaning and enrichment solutions if necessary.

Underestimating Organizational Impact

Integrating an AI solution modifies business processes and work habits. Anticipate this impact with your agency and plan appropriate support to facilitate adoption.

French AI Market Trends

Digital Sovereignty and Trust

French companies are strengthening their technological sovereignty requirements. This trend favors agencies offering French cloud infrastructures and respecting European standards.

AI Democratization

AI becomes accessible to SMEs through modular solutions and adapted economic models. This democratization opens new growth opportunities for companies of all sizes.

Responsible and Ethical AI

Integrating ethical and environmental criteria in AI development becomes the norm. Leading agencies propose optimized architectures, less energy-consuming and respectful of responsible AI principles defined by the EU.

Towards a Sustainable Strategic Partnership

Your AI agency choice determines your digital transformation success. Beyond technical expertise, prioritize a partner sharing your vision and capable of adapting to your evolving needs.

At Daijobu AI, we support Parisian companies in their AI transformation with a personalized approach, sovereign infrastructure, and transparent economic model. Our proven methodology and sector expertise guarantee successful and sustainable projects.

Organize in-depth interviews with several agencies, compare their approaches, and prioritize transparency. AI investment represents a major strategic challenge: your partner must match your ambitions.

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Ready to launch your AI project? Discover our approach and schedule a meeting with our experts for a personalized diagnosis of your AI opportunities.

At Daijobu AI, we are proud to announce our support for the EuroStack initiative by signing the recent open letter to European Commission President Von der Leyen calling for stronger commitment to sovereign digital infrastructure. As a young French AI startup founded just last year, our decision to join over 200 European companies and associations in this important call to action reflects our core values and strategic vision.

Alignment with Our Mission

Since our founding, Daijobu AI has been committed to democratizing access to custom AI by providing businesses with efficient, personalized, and scalable tools. Central to our approach is our “trust-first philosophy” where clients retain full ownership and control over their data through transparent tools. This philosophy naturally aligns with the EuroStack initiative’s emphasis on European digital sovereignty.

The open letter highlights that “Europe’s current multiple dependencies create security and reliability risks, compromise our sovereignty and hurt our growth.” This concern resonates deeply with us. As developers of tailored AI models trained exclusively on client data, we understand firsthand the critical importance of data sovereignty and the need for European businesses to maintain control over their digital infrastructure.

The Growing European AI Market Needs Sovereignty

Our market analysis shows that AI will contribute €15.7 trillion to the global economy by 2030. In France alone, the AI market is valued at €4.86 billion in 2024, with projections reaching €17.6 billion by 2029. These figures represent enormous potential for European innovation and economic growth – but only if we build the right foundation of digital sovereignty.

As the letter states, Europe “needs to take proactive industrial action” rather than simply regulating itself out of its current position. At Daijobu AI, we’re already taking action by providing businesses with AI solutions hosted on sovereign infrastructure in France. This approach ensures that European businesses can benefit from advanced AI capabilities while maintaining data security and regulatory compliance.

Our Commitment to a Sovereign European AI Ecosystem

The open letter calls for several key actions that align perfectly with our business model and vision:

1. Creating demand for European solutions – Daijobu AI’s leasing model makes custom AI accessible to businesses of all sizes, helping drive adoption of European AI solutions.
2. Supporting a “pooling and federating” approach – Our internally developed “Daij” framework accelerates AI development, contributing to the ecosystem of European technical assets.
3. Prioritizing services with strong adoption prospects – Our focus on tailored AI models for specific business needs addresses real market demands.
4. Developing harmonized requirements for sovereign cloud services – Our commitment to hosting all solutions on sovereign infrastructure in France supports this goal.

A Call for Collaborative Action

At Daijobu AI, we’re building a leader in providing AI technology building blocks for businesses. Our vision of “becoming for AI what Cloudflare is for the web — a major, yet invisible, player in modern infrastructure” requires an ecosystem where European digital sovereignty is valued and protected.

We firmly believe that supporting initiatives like EuroStack is not just about politics or regulations—it’s about building a sustainable, trustworthy, and competitive European digital landscape. By signing this open letter, we stand with fellow European innovators calling for concrete actions to transform tech sovereignty ambitions into reality.

The time for radical action is now. Europe has the talent, capabilities, and vision to lead in the digital age, but only if we work together to create the conditions for European technology companies to thrive. At Daijobu AI, we’re committed to playing our part in building a sovereign, innovative, and competitive European AI ecosystem.

As our CEO Gautier Uchiyama often says, “AI should adapt to your business, not the other way around.” The same principle applies to Europe’s digital infrastructure—it should serve European values, businesses, and citizens first. That’s why we’ve proudly added our name to this critical initiative.