Notes from the lab: agents, sovereign infrastructure, data, visibility and PropTech.
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AI governance in a company is a set of policies, roles, and control mechanisms that enable responsible AI deployment, compliant with the AI Act and RODO. A practical guide.
Can AI conduct research independently? 2026 analysis: hypothesis generation, interpretability, AI Act, and human oversight in research systems.
How to implement AI in a call center: call transcription, real-time agent assistant, voice bot, and compliance with RODO and AI Act.
Where AI actually boosts sales and reduces team workload in online stores — 24/7 support, offer personalization, product descriptions. No fluff.
How to implement AI in corporate training: personalized learning paths, knowledge agents, RAG on materials, GDPR and AI Act in practice.
How to implement AI in content marketing: RAG architectures, quality guardrails, PII, GDPR, and AI Act for content marketing teams in 2026.
AI in B2B sales automates lead qualification, SDR sequences, and ICP scoring. Concrete implementation patterns, guardrails, and limitations for Polish teams.
How to maintain the relevance of a RAG knowledge base: strategies for incremental reindexing, document versioning, and knowledge drift detection in production environments.
How to protect personal data before sending it to AI models. PII masking patterns, pseudonymization, GDPR, and practical architecture for businesses.
AI assistant security audit 2026: checklist covers prompt injection, PII leakage, tool permissions, rate-limiting, and RAG database vulnerabilities.
How to implement AI customer service automation, choose the right scope, and measure real results. Concrete patterns, costs, and limitations.
An agent acts, not just talks — so it needs boundaries. How to give AI agency without losing control: allow-list, confirmations, audit trail.
Concrete takeaways on AI agents, sovereign infrastructure and visibility in AI models — no spam.
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