How to Govern and Control AI Agents: A Practical Agent Governance Guide
Six control layers, an agent inventory, monitoring and incident response to run AI agents safely in your company. A practical guide from live projects.
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For leaders planning AI investments: vendor selection, timelines, cost drivers, security and implementation guides.
Six control layers, an agent inventory, monitoring and incident response to run AI agents safely in your company. A practical guide from live projects.
Read moreWhat is AI-powered process management? How AI agents track orders and work orders, flag delays and prepare reports, with lessons from a live project.
Read moreHow European and US companies can work with an AI agent team in Türkiye: time zones, GDPR and data transfers, how to evaluate a partner and how to start.
Read moreHow AI agents find and qualify B2B customers, where they go wrong and how to stay GDPR/KVKK compliant. Lessons from a project that lifted acquisition by ~70%.
Read moreHow AI automates public tender tracking, specification analysis and deadline management. Lessons from a project that automated about 90% of manual tender work.
Read moreHow to choose an AI consulting company: 10 selection criteria, red flags, engagement models, cost drivers and the questions to ask in your first meeting.
Read moreA practical generative engine optimization (GEO) guide: how brands get cited in ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews, beyond SEO.
Read moreHow does an enterprise AI assistant project run? Phases and typical timelines, one-off and recurring cost components, build vs. buy, and why projects fail.
Read moreWhat AI agents for business process automation are, how they differ from RPA and chatbots, how to add guardrails and human review, and how to measure results.
Read moreHow to run GDPR and KVKK compliant AI in your company: data classification, masking, cross-border transfers, vendor contracts and EU AI Act awareness.
Read moreHow to choose between OpenAI GPT, Anthropic Claude and Google Gemini for enterprise use: data residency, cost, context length, tool use, compliance, lock-in.
Read moreWhat is RAG (Retrieval-Augmented Generation) and how does it work? A guide to using enterprise data securely with LLMs, with citations and access control.
Read moreA practical 90-day enterprise AI transformation roadmap: choosing the right use case, preparing data and governance, running a pilot and moving to production.
Read moreWe assess your processes and data landscape together to identify where AI will create the most value for your organization, and define a clear implementation roadmap and data-security requirements.