Why we’re building it. Why it matters. Why join the waitlist now. Over the last year, AI prototyping has become incredibly fast. But one thing hasn’t improved at the same pace: production. Teams can build impressive demos in hours… and then spend weeks trying to make them stable,
When organizations consider adopting AI, they often picture complex initiatives: process automation, multi-system integrations, end-to-end orchestration, or full workflow redesigns. Yet the projects that create the strongest initial momentum — and the highest level of internal trust — are usually the simplest. Deploying a RAG engine to make regulatory documents searchable and
Au cours des derniers mois, nous avons accompagné plusieurs organisations dans l’implémentation concrète de solutions fondées sur l’intelligence artificielle. Ces projets, menés dans des contextes variés (industrie, agriculture, services, énergie, finance…), ont renforcé notre conviction : pour réussir, l’IA doit être introduite avec méthode, clarté et exigence technique.
Context. In highly regulated sectors (banking/insurance, healthcare, energy, pharma, public services), it’s tempting to “plug in a RAG” so a LLM can answer from internal documentation. Poorly framed, results disappoint: inaccurate answers, compliance risks, unpredictable latency, low adoption. Built correctly, RAG becomes a verifiable knowledge system that shortens
Introduction Since generative AI tools like ChatGPT, Claude, and Copilot have entered public awareness, two dominant narratives have emerged: one predicting massive job losses, the other seeing transformative economic opportunity. A new study published by Yale’s Budget Lab, titled “Evaluating the Impact of AI on the Labor Market: Current
The world doesn’t need AI everywhere Artificial intelligence is no longer a promise—it’s a reality. Every week, new platforms and tools claim to “revolutionize everything.” From AI-generated emails to automated decision-making, we live in a time where it feels like the answer to every question is simply:
Managing regulatory filings and internal healthcare documents is time-consuming, error-prone, and resource-intensive. Teams handling 12,000 documents per year can spend 20 weeks manually processing them, creating inefficiencies and compliance risks. NVMD SmartComply is an AI-driven regulatory automation tool designed specifically for the healthcare industry. It streamlines compliance, ensures data
Agentic artificial intelligence represents a major technological breakthrough that far exceeds traditional chatbots and copilots. The global market reaches $5.2 billion in 2024 with explosive growth of 43.8% annually, positioning agentic AI as the next enterprise revolution. Unlike current reactive AI tools, these autonomous systems plan, execute, and
NVMD (nvmd.tech) Partners with Docugami to Revolutionize Document Data Extraction and Analysis Keywords: NVMD, Docugami, document intelligence, document AI, data extraction, Knowledge Graph, RAG, document engineering, enterprise AI NVMD x Docugami: An Exceptional Partnership for Document Innovation NVMD (nvmd.tech), the French AI implementation company specializing in ROI-driven solutions,
How Retrieval-Augmented Generation (RAG) systems are concretely revolutionizing business processes across all sectors RAG (Retrieval-Augmented Generation) is no longer an emerging technology – it has become a strategic pillar for companies seeking to transform their mountains of document data into competitive advantage. Beyond marketing promises, RAG deployments now generate measurable results
Use Case
Context & Challenge A leading streaming entertainment provider (26M+ subscribers) investing $1.3B annually in digital transformation faced critical technical challenges after 18 months of explosive growth: Infrastructure Pain Points • Complex hybrid cloud architecture: AWS primary + Nutanix critical workloads, managing 15,000+ servers • Unpredictable audience spikes: 70,000 connections/minute
Insights
Enterprise data infrastructure mistakes represent the single largest barrier to successful AI implementation, costing U.S. businesses $3.1 trillion annually in poor data quality alone while contributing to an 87% failure rate for AI projects reaching production. Research from MIT, McKinsey, and industry leaders reveals that companies like IBM
News
At NVMD, we observed a clear trend: companies buy AI tools but struggle to implement them effectively. Prototypes are often abandoned, integrations fail, and teams depend heavily on external vendors. The promise of AI too often remains theoretical. To address this, we are officially launching the NVMD AI Squad, a
Insights
Common Question: Why isn't my AI project generating any return on investment? Short Answer: A MIT study reveals that 95% of enterprise AI projects generate zero return on investment, despite $30-40 billion in spending. The main reason? Companies multiply internal pilots without ever scaling, while those who buy
Insights
How to avoid the most common pitfalls that can skyrocket your cloud costs and slow down your AI projects Introduction Preparing AWS infrastructure for artificial intelligence has become a strategic imperative for many enterprises. However, our field audits reveal that 85% of "AI-ready" cloud architectures have critical flaws
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Published by NVMD | August 2025 | Strategic Partnership Announcement Executive Summary Partnership Announcement: NVMD has formed a strategic partnership with SingleStore, the world's fastest distributed SQL database for real-time AI applications, to deliver unprecedented performance in enterprise AI implementations. The Challenge: Enterprise AI systems require instant data access and
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Published by NVMD | July 29, 2025 | Featured in Le Dauphiné Libéré Media Recognition: NVMD's AI Transformation Approach Gains National Attention We're excited to share that NVMD has been featured in Le Dauphiné Libéré, one of France's leading regional newspapers, highlighting our rapid growth and
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Published by NVMD | August 2025 | Based on analysis of enterprise AI agent implementations and industry research Executive Summary The AI Agent Opportunity: AI agents represent the next frontier in enterprise automation, with the potential to generate $450 billion in economic value by 2028 according to industry research. Current State: 37%
Insights
Published by NVMD | August 2025 | Based on evaluation of 100+ AI project proposals Executive Summary Key Problem: Enterprise leaders receive an average of 10 "revolutionary AI" pitches per week, but lack systematic frameworks to evaluate which projects will deliver real value. Solution: NVMD's 6-step AI Project
Insights
Published by NVMD | August 2025 | Based on analysis of 50+ enterprise AI projects Executive Summary Key Finding: 70% of enterprise AI projects fail before reaching production, with architecture decisions being the primary cause of failure. Data Source: Analysis of 50+ enterprise AI implementations conducted by NVMD between 2023-2025. Success Rate