FAQ: understand everything about AI in business

Classic AI follows predefined rules or statistical models for specific tasks (image recognition, fraud detection). Generative AI, like Claude (Anthropic), GPT-4o (OpenAI) or Mistral (Mistral AI), generates new content: text, code, analysis, action plan. It understands natural language and can reason about open problems. This is what makes it a transversal tool applicable to almost all business processes.

There is no minimum threshold. Most companies can start with a pilot project on 1 to 2 processes, regardless of their size or technological maturity. What matters is identifying the right entry point: this is precisely the role of a AI audit. We have accompanied artisans as well as industrial groups.

AI automates tasks, not positions. In the vast majority of cases, it frees your employees from repetitive, low-value tasks so they can focus on human interactions, creativity and complex decision-making. Our approach is to co-construct new workflows with your teams, never against them.

For a first measurable result : 4 to 6 weeks after the start of a mission. Quick wins (automation of an incoming email, automatic summary of meetings, assisted writing) can be operational in less than 2 weeks. Structuring projects (deployment of an autonomous agent, private LLM) require 2 to 4 months. The ROI is defined and measured from the start.

No. Most of the solutions we deploy are designed to be used by non-technical people via a conversational interface or an existing business tool. We train your teams on new workflows, not on technique. If your organization wants to develop technical autonomy, we also offer expert training adapted.

One AI audit is a structured analysis of your business processes to identify high-ROI automation opportunities. It maps your flows, evaluates the potential for AI for each task, benchmarks suitable models and produces a prioritized roadmap. This is the only way to avoid investing in the wrong direction and to get defensible numbers to convince your management or board.

A Flash Audit (2 days, 2 targeted processes) starts at €2,500 excl. tax. A complete audit for an SME with 20 to 100 employees ranges from €5,000 to €10,000 excl. tax depending on the number of processes analyzed. Each mission includes a transparent quote before starting. Regional financing schemes (business consulting aid) can cover 50 to 70% of the cost depending on your department.

Three deliverables: (1) a structured report listing all identified AI opportunities with their estimated ROI, (2) a prioritized roadmap over 12 months with indicative budget per step, (3) a feedback session with your management committee to validate priorities and build the implementation plan. The report is your property: you can have it implemented by any provider.

No. The audit is based mainly on interviews with your teams, observation of your processes and analysis of your existing tools. We do not need access to your data or IT system. If you want us to analyze data volumes (to refine ROI estimates), we use anonymized samples in isolated environments.

Claude 3.5 Sonnet (Anthropic) excels in complex reasoning, nuanced analysis and long multi-step tasks - it is the preferred model for the autonomous agents and in-depth document analysis. GPT-4o (OpenAI) is native multimodal: it natively handles images, screenshots and heterogeneous documents. For Microsoft integrations, GPT-4o via Azure OpenAI Service is often the most consistent choice in terms of compliance and DPA.

Mistral AI is a French startup founded in 2023 that develops high-performance and open LLM models. Mistral Large is available for on-premise deployment on French infrastructure via OVHcloud, without data transfer outside the EU. This is the reference solution for regulated sectors (health, finance, defense, public authorities) subject to strict GDPR requirements on data location.

Meta Llama 3.1 (Meta AI) is an open-source model that can be deployed entirely on your private infrastructure - dedicated cloud or on-premise. Its main advantage: zero marginal cost (you only pay for the infrastructure) and complete customization via fine-tuning on your own data. Ideal for large volumes or highly sensitive data.

Google Gemini 1.5 Pro stands out for its exceptional context window (up to 1 million tokens), making it the reference model for RAG (Retrieval-Augmented Generation) use cases on very large document bases. If your organization uses Google Workspace (Drive, Docs, Gmail), Gemini for Google Workspace is the most natural and natively supported integration.

DeepSeek R1 (DeepSeek) is a structured reasoning model available at a much lower cost than OpenAI or Anthropic models. It excels in financial analysis, mathematical reasoning, and structured analysis tasks. Its performance-to-cost ratio makes it an excellent choice for high-volume automations where the cost per query is critical.

Perplexity AI combines a real-time web search engine with a language model. Unlike Claude or GPT-4o which rely on trained knowledge up to a cut-off date, Perplexity accesses real-time news. It is particularly useful for automated competitive monitoring, sector trend tracking and sourced and verifiable documentary research.

The choice depends on 4 criteria: (1) the nature of the task (reasoning, vision, research, code), (2) your GDPR and sovereignty constraints, (3) the volume of processing and acceptable marginal cost, (4) existing integrations in your stack. We never recommend a single model - we benchmark on your real use case and choose the most suitable one. Consult our complete comparison of LLM models.

The RPA (Robotic Process Automation) automates fixed and predefined sequences. It fails as soon as a format changes or contextual decision is required. TheAI automation understands content, adapts to context and makes micro-decisions. A Make or n8n workflow enriched with Claude can read an email regardless of its formulation, understand the intention and act accordingly, where an RPA would have returned an error.

One autonomous AI agent is a system that receives an objective and executes it from start to finish, making its own decisions at each step: it can call APIs, consult databases, write documents and send messages without human intervention on standard cases. Claude 3.5 Sonnet (Anthropic) and GPT-4o (OpenAI) are the most capable models for complex multi-step agents.

The RAG is a technique that connects an AI model to your internal documentary database. When you ask a question, the system first searches for relevant documents in your database, injects them into the model context, and generates a sourced response. Result: an AI assistant that responds by citing your own procedures, contracts, and reports, and not generic information. Google Gemini 1.5 Pro excels in large-scale RAG thanks to its 1M token context window.

All our automations integrate reliability mechanisms: (1) configurable human fallback if AI is uncertain, (2) complete logs of each action for audit, (3) alert thresholds that notify your teams as soon as the error rate exceeds a predefined level, (4) extensive testing on real data before deployment. No automation goes into production without being validated on boundary cases.

Make (ex-Integromat) offers the best granularity for complex workflows with many conditions and branches - our recommendation for SMEs. n8n is open-source and can be self-hosted for organizations that want to keep their workflows on their infrastructure. Zapier is the simplest to use for simple automations with few steps, but lacks flexibility for complex cases.

Yes, under conditions. The use of cloud AI models (Claude API, GPT-4o API) requires the signing of a DPA (Data Processing Agreement) with each provider, these agreements exist and are available. For highly sensitive data (health data, personal data at risk), we recommend either on-premise models (Mistral AI, Meta Llama 3) or Azure OpenAI deployments with EU Data Boundary clauses. Each mission includes a GDPR risk analysis.

No, if you use professional APIs. Anthropic (Claude API), OpenAI (API with DPA), Mistral AI (API) and Google (Vertex AI) do not reuse your prompt data to train their models under their enterprise contracts. Public interfaces (Claude.ai free, ChatGPT free) have different policies: we never recommend them for professional use with sensitive data.

One Private LLM is an AI model deployed on your own infrastructure (dedicated servers or private cloud): your data never leaves it. Common solutions: Mistral Large on OVHcloud or other French infrastructure, Meta Llama 3.1 on your own servers. You need it if your sector requires it (health, defense, regulated finance), if your data is covered by business secrecy or if your processing volume makes API costs prohibitive.

Our deployments systematically include: API key management in a secure vault, secret rotation, integrated SSO authentication with your company directory (Active Directory, Google Workspace), communication encryption, access and usage logs. We document each access in a security plan provided to your RSSI before deployment.

Our method: (1) measure the current time spent on targeted tasks × average hourly cost, (2) estimate the time saved after automation, (3) subtract AI deployment and maintenance costs (often 50 to 200€/month for APIs). A typical ROI: automating 5 hours/week of work at 40€/hour = 10,400€/year saved, for a deployment at 8,000€ → positive ROI in less than 10 months.

Several options depending on your situation: (1) France 2030 : subsidies for the digital transformation of industrial SMEs, (2) Digital consulting support of regions: up to 50% funding for consulting missions (including AI audit), (3) Innovation tax credit for companies that develop proprietary AI solutions, (4) BPI loans for digital transformation projects. Contact us for an analysis of your eligibility.

Budgets vary greatly depending on the scope. Indicatively: a first pilot project (audit + implementation of an automation): 8,000 to 20,000€. A complete transformation over 12 months (audit, 3 to 5 automations, AI agent, team training): 30,000 to 80,000€ for an SME of 20 to 100 people. API recurring costs are generally 200 to 2,000€/month depending on the volume.

Initiation (Level 1) : 1 day to understand AI and use everyday tools (ChatGPT, Claude, Gemini) from the next day. Mastery (Level 2) : 2 to 3 days to automate workflows, master advanced prompt engineering and integrate AI into business tools. Expert (Level 3) : customized program for executives and CIOs, building a complete AI roadmap with KPIs and governance.

Yes, our training sessions are organized in partnership with certified Qualiopi training organizations, which allows for financing by your OPCO. The procedure: we establish a quote, your OPCO validates the financing before the start of the training. The processing time is generally 2 to 4 weeks. Contact us for a financing file.

Yes, systematically. All our in-company training sessions are personalized with use cases from your industry. A workshop for a sales team does not resemble a training session for a legal team or a production team. Sectoral adaptation is included in all our in-company training, without extra cost.

A Flash audit: 48 hours. A complete audit: 2 weeks. Integration and automation missions: 4 to 12 weeks depending on complexity. Strategic retainers: 6 to 12 months with 2 to 4 days of monthly presence. The first measurable results are generally available within 6 weeks of starting an implementation mission.

No. We are not commercial partners of any AI provider. We do not receive any commission on Claude, GPT-4o, Mistral or other licenses. We always select the most suitable model for your use case and constraints: a condition sine qua non for objective advice. You can check: our recommendation varies systematically depending on the client context.

We intervene in all sectors: commerce and distribution, B2B services, industry, health and paramedical, real estate and construction, finance and accounting, communication and marketing, legal and HR, craftsmanship and construction, hospitality. Our approach adapts to each sector: AI use cases, recommended tools and success metrics are always contextualized.

Three steps: (1) fill out our contact form or call us directly, (2) we schedule a 30-minute framing call (free, no commitment) to understand your situation and challenges, (3) we provide you with a proposal within 48 hours with the recommended mission type, planning, and budget. Start-up is possible within 2 weeks after signature.