Why standalone AI demos rarely turn into value
Plenty of organisations run impressive AI proofs-of-concept that never reach daily work. The gap is integration: connecting AI to real data, existing software and actual processes, with the security and reliability production demands.
I bridge that gap: where to plug AI into your stack, how to use APIs and assistants, how to feed AI your own data safely (including RAG approaches), and how to embed it in automated workflows. AI moves from demo to dependable everyday tool.
Value lives in the workflow: AI that isn't integrated into real work stays an impressive demo.