Why AI Projects Die Between the Demo and Production
Confusion around enterprise AI integration is no longer unusual. Executives develop high expectations, a technical team produces an impressive demo within weeks, early users see the potential—and then the project gets close to production. Costs rise, latency appears, security questions surface, retrieval quality becomes inconsistent, and an architecture that worked for a handful of developers behaves very differently when hundreds of employees arrive.
Read it →