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ARTIFICIAL INTELLIGENCE
Generative AI, RAG and intelligent automation.
Use AI where it creates real value: productivity, personalization, analysis, content and customer experience.
Content, analysis and assistants.
Reliable, contextual answers.
AI + workflows for productivity.
Not an AI that improvises. An AI that understands your business.
PROJECTS
ARTIFICIAL INTELLIGENCE
AI is a powerful addition to the toolbox, but it is not a strategy. I focus on practical uses: knowledge access, productivity, analysis, content support, customer experience and intelligent automation.
OpenAI, Claude and other models become more useful when they work with company context, rules and verified information. This can support internal teams, customer service, sales and marketing workflows.
The objective is not an AI that improvises. It is an AI system designed around a defined task and reliable sources.
Retrieval-Augmented Generation connects a model to a knowledge base. Documents, product catalogs, procedures, pages or CRM information can be indexed in a vector database such as Pinecone, retrieved semantically and supplied to the model before it answers.
This makes responses more contextual, traceable and easier to update than relying on model memory alone.
Start with the use case, data and expected value. Then choose the architecture.
AI can classify, extract, summarize, draft and decide within controlled boundaries. Combined with CRM, APIs and automation tools, it can remove repetitive work and create new customer experiences.
The same discipline used for SEO and GEO improves RAG: clear, structured and contextualized information is easier for machines to retrieve and use correctly.
FAQ
Direct answers to the questions I am asked most often.