ConceptsCan AI predict bitcoin? We tested Mistral's Timestral
We tested Timestral, Mistral's forecasting model, on eight years of bitcoin data. It cannot forecast the price, but it beats every model we tried on volume.
10 min
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ConceptsWhy Anthropic replaced git with Scion (and what to take from it)
Anthropic swapped git for Scion to handle 30,000 merges a day, with AI agents as its main users. Why it happened, what Scion is worth and what comes after git.
11 min
AnthropicGitAI Agents
GuideHow AI works: the 10 concepts to understand before you sign
Neural networks, tokens, training, fine-tuning, hallucination, LLMOps: the ten concepts that explain where your AI budget goes and where your dependency begins.
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GuideChatGPT Enterprise: 5 simple tips to make your credits last
ChatGPT Enterprise credits running out too fast? The model you pick matters far more than the length of your questions. Five simple tips to make them last.
7 min
ChatGPTAI costsModel selection
Digital SovereigntyOVHcloud's AI strategy: what Octave Klaba's plan is worth
OVHcloud is announcing its own LLM and wants the whole AI stack. What already exists (GPUs, AI Endpoints), what is still unproven, what IT leaders can learn.
11 min
ConceptsClaude Mythos: AI finds flaws faster than we can patch them
Claude Mythos and other AI models have flooded Mozilla, Bank of America and the Linux kernel with flaws to fix. What it costs, and why patching takes hours.
12 min
CybersecurityAnthropicOpen source
Digital SovereigntyCoreWeave, Mistral AI's subcontractor: should you worry?
For all its products, Mistral AI declares just two compute operators: its own servers and CoreWeave, whose debt is in distress. What a default would change.
11 min
ConceptsChatGPT watermark: how textGrain works
OpenAI is adding an invisible watermark to ChatGPT text in Europe. How textGrain works, who is affected, and can it be detected or removed?
8 min
ChatGPTOpenAIAI Act
Digital SovereigntyWho owns Hugging Face, Mistral AI and Doctolib? The real owners of 14 French tech companies
Nvidia is buying into Doctolib and acquiring Hugging Face. Who really owns France's tech champions? Control, legal home and data hosting, checked.
13 min
ConceptsAI self-replication: Anthropic's study on AI worms
Can an AI replicate itself? What Anthropic tested on connected devices, AI worm versus AI virus, the study's limits and what businesses can do about it today.
11 min
ConceptsAI Distillation: Everyone Blames China, Everyone Does It
OpenAI and Anthropic accuse Chinese labs of distilling their models. Yet Meta, Google, Mistral and even Musk's xAI distill too. Here is what we actually know.
11 min
DistillationDeepSeekOpenAI
GuideLLM gateway: OpenRouter, LiteLLM or build your own?
LLM gateway or AI gateway: what it does, OpenRouter vs LiteLLM, what it costs and where your data goes. Our own price and speed readings included.
9 min
ConceptsHow many documents can a RAG system handle?
A home-made RAG tops out at a few thousand documents per agent, fewer if they look alike. An agentic RAG that filters first handles over 100,000.
GuideMistral OCR: cut your bill 10x with open weights
Mistral OCR costs $4 per 1,000 pages. An open-weight OCR on a European GPU drops to $0.15 and stays sovereign. Benchmark, break-even point and pitfalls.
10 min
GuideJev reranker for RAG reranking: how we use it in production
Jev as a RAG reranker: how we use TypeSafe's AI model in production, the scores it gives, the chunks it keeps, response time and cost.
8 min
ConceptsHybrid search: the 6 ways to find a piece of information
Semantic, keyword, business tools, database queries, document catalog, tailored processing: the six paths an agent chains to find the right answer.
Digital SovereigntyBest French AI for enterprises in 2026: 14 vendors put to the sovereignty test
Fourteen French enterprise AI vendors checked against public sources: who owns the capital, who hosts your data, who runs inference.
GuideAI Inference: the 7 ways to run your models in the enterprise
Enterprise AI inference: 7 approaches compared, from buying GPUs to a turnkey provider. Real costs, sovereignty, latency and how to choose.
11 min
GuideEnterprise AI agents: use cases and real costs
Enterprise AI agents: the definition, what an agent can really do, the method that gets it into production, and what it actually costs.
GuideInternal company chatbot: how to scope the project right
Internal company chatbot: what it is really for, how it differs from a website chatbot, the classic pitfalls and the conditions for success.
GuideKnowledge management: why your initiatives fail, and what AI changes
Why knowledge management initiatives fail, what AI really changes about managing what a company knows, and what it will never change.
GuideEnterprise AI SLA: one AI provider for your agents is not enough
Why one provider is not enough for an enterprise AI SLA. Compare commitments, multi-provider gateways and fallbacks for RAG and AI assistants.
3 min
GuideSaaS chatbot: product support, data, and AI actions
A chatbot built into a SaaS product cuts tickets, limits churn, and surfaces upsell opportunities. Product support, data, and actions: a guide by maturity level.
GuideData analysis tools: which family for which need in 2026?
Excel, Power BI, Python, conversational AI: a comparison of data analysis tool families to help you pick the right one for your needs.
GuideManagement control: how to combine Excel, Power BI dashboards and AI?
Excel, Power BI dashboards or conversational AI: which tool for your management control, financial reporting and data analysis? A guide to choosing.
GuideHow to generate qualified leads with a company website?
Starting a conversation quickly and making a strong first impression are essential to building a lasting relationship.
GuideContextual AI for your company: 6 concrete productivity gains
Discover 6 concrete productivity gains that contextual AI with RAG can bring to a company by structuring and sharing its knowledge more effectively.
GuideEnterprise RAG: 5 mistakes that show up after the POC
An enterprise RAG is relatively easy to prototype. Making it a useful, stable product is a much bigger challenge. Here are the five most common production pitfalls—and how to get ahead of them.
GuideGetting AI automation right: use as little AI as possible
What is AI automation? Benefits, examples, tasks worth automating, and key steps to do it right while using as little AI as possible in production.
ProductYour databases are a gold mine, AI gives you the shovels
Juggling enterprise systems, getting a simple answer often takes twenty minutes (or a Teams ping to the “person who knows”). Your real data lives in structured databases: it’s often reliable, up to date… but also inaccessible. Most companies seem to overlook it, yet AI can query it in plain language and cross-reference documents and databases in seconds.
AIOn-premise LLM and RAG for the enterprise: what €60k really buys you
On-premise LLM in 2026: GPU prices, memory per model, full TCO and break-even against the same model via API. Figures to decide between Make and Buy.
12 min
GuideMCP (Model Context Protocol): definition and role in agentic AI
What is MCP in agentic AI? Definition of the Model Context Protocol, how it works, and how it relates to function calling, skills and MCP Apps.
ConceptsHow a Failed Demo Forced Us to Rethink Our Embedding Strategy
Slow embedding APIs and vendor lock-in: our production lessons, and why ATG now calls Qwen 3 Embedding 8B on several providers at once.
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TutorialHow RAG Transforms Your AI into an Expert on Your Business
RAG and LLM: definition, how it works, choosing the model. The guide to connecting an LLM to your internal documents and enterprise data.
ConceptsOpen-weight vs open-source: what an open-weight model really is
Open-weight or open-source model: definition, differences, licences and enterprise use. Why an LLM is almost never open-source the way Linux is.
Digital SovereigntyWhat if the United States Turned Off Your Digital Tap?
How dependence on U.S. infrastructure exposes Europe to growing strategic risks - and what to do to protect yourself.
3 min