One thing I’ve learned recently: Adding an LLM API is the easy part Butbuilding an AI feature that people can actually trust inside a real product is much harder.In one of the SaaS platforms I’m working on, we built a Smart Upload workflow for energy and compliance data.The basic idea sounds simple:Upload CSV/Excel → AI reads it → structured data is created.But the real workflow became much more interesting:Upload → Analyse → Review → Correct → Re-analyse → Validate → ImportA few lessons stood out.AI output should not immediately become application data.We treat the AI result as a proposal. The user can review detected assets, energy types, units, dates and consumption values before anything is finally imported.Human corrections are valuable context.If the AI misunderstands something, the user can give an instruction such as:“The unit is kWh.”or“The reporting period is January to March.”The system can then analyse the file again while preserving corrections the user has already made.Th...
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