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Specific write-ups on the decisions that decide whether AI and enterprise software systems survive production — written from client delivery, not from a content calendar.
Specific write-ups on the decisions that decide whether AI and enterprise software systems survive production — written from client delivery, not from a content calendar.
Short, specific write-ups on the decisions that determine whether an AI system survives contact with production: retrieval versus fine-tuning, latency budgets for voice, where guardrails belong, and how to modernize a system that cannot go down. Every article states the trade-off and the rule we apply, not a list of features.
When retrieval is enough, when fine-tuning actually earns its cost, and how to tell the difference on your own data before spending a budget.
Latency budgets, barge-in, escalation paths, evaluation sets and telephony integration — the engineering that separates a demo from a phone line customers accept.
Want one of these sooner? Tell us which problem you are solving and we will prioritise it.
Every piece is drawn from delivery work: our case studies across healthcare, manufacturing, financial services, retail, logistics, insurance and telecom, plus our own products — iCare, Callora and TaskEdge.