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AI & Blockchain Innovation Partner
Data Quality for Generative AI: A Practical Guide for Enterprise Teams
Generative AI can only work with the data you give it. When that data is wrong, outdated or duplicated, the model repeats those flaws in fluent sentences that sound right. The numbers show how common the gap is. A Gartner survey of 1,203 data management leaders found that 63% of organizations either lack the right […]
AI Data Readiness: How to Test Your Data Before You Build AI
Key Takeaways Most AI projects do not fail in the model. They fail in the data feeding it. Gartner's research puts numbers on that. In a 2025 analyst Q&A, Gartner reported that 63% of organizations either lack the right data management practices for AI or are unsure they have them. The same source predicts that […]
AI Development for Financial Services: A Practical Guide for Banks and Fintechs
Most banks and fintechs already use AI. Building it well is the hard part. The Bank of England and the FCA found that 75% of UK financial firms were already using AI in 2024, with another 10% planning to start within three years. In the same survey, 46% of firms said they only partly understood […]
Generative AI Development for Enterprise: A Practical Guide
Key Takeaways Almost every organization now uses AI somewhere. McKinsey's 2026 State of AI survey found that nearly nine in ten use it regularly in at least one business function. Yet only 37% report any EBIT impact, and about 6% qualify as AI high performers. Generative AI shows the same gap. Gartner predicted that at […]
Computer Vision Development for Manufacturing: A Practical Build Guide
Key Takeaways Factories know what a bad part costs. The hard part is catching it at line speed, on every shift. McKinsey estimated that AI-based visual inspection may raise defect detection rates by up to 90% compared with human inspection. A later McKinsey review of the World Economic Forum's Lighthouse factories found that 77% of […]
AI Governance for Enterprise Applications: A Practical 2026 Framework
Enterprise AI has moved past the stage where governance can be handled by a policy document and an annual compliance review. AI is now embedded inside applications, connected to enterprise data, making recommendations, calling tools, and increasingly taking actions across business systems. The scale of that change is significant. Gartner forecasts that 40% of enterprise […]
AI Integration with ERP and CRM: A Practical Guide for 2026
Key Takeaways Most companies now use AI somewhere. Few have connected it to the systems where business actually gets recorded. McKinsey's State of AI survey found that 62% of organizations are at least experimenting with AI agents, yet no more than 10% report scaling agents in any single business function. The blocker is usually data, […]
Enterprise AI Architecture: 6 Layers and How to Build It
Key Takeaways Most organizations use AI now, but few have made it work at scale. McKinsey's 2025 survey found that 88% of organizations use AI in at least one business function, yet only 7% say AI is fully scaled. In its 2026 survey, 80% of respondents said AI improved their personal productivity, but just 6% […]
How to Evaluate AI Development Companies: A 6-Criteria Scorecard
Key Takeaways Picking the wrong AI development company is expensive, and the odds are not friendly. RAND notes that by some estimates more than 80% of AI projects fail, twice the failure rate of IT projects without AI. McKinsey's 2026 State of AI survey of 1,719 respondents found that 37% report any EBIT impact from […]
RAG vs Fine-Tuning: How to Choose the Right LLM Optimization Strategy
The RAG vs Fine-Tuning debate is often framed as a choice between two competing ways to make an LLM “smarter.” That framing is misleading because the two techniques solve fundamentally different problems. RAG changes what the model can access at inference time. Fine-tuning changes how the model behaves. If your AI system gives outdated answers […]
AI Development Process: 7 Stages From Idea to Production
Key Takeaways Introduction: Why the AI Development Process Matters Many AI projects stall for reasons that have little to do with the model. In a Gartner survey of 644 organizations run in late 2023, only 48% of AI projects made it into production, and the average trip from prototype to production took 8 months. The […]
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02.06.2025
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